Add SetFit model
Browse files- 1_Pooling/config.json +10 -0
- README.md +449 -0
- config.json +24 -0
- config_sentence_transformers.json +9 -0
- config_setfit.json +4 -0
- model.safetensors +3 -0
- model_head.pkl +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +59 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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README.md
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---
|
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library_name: setfit
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tags:
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- setfit
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- sentence-transformers
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- text-classification
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- generated_from_setfit_trainer
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base_model: sentence-transformers/paraphrase-mpnet-base-v2
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metrics:
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- accuracy
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widget:
|
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- text: BI 8U-Q10-AP6X2-V1131 SENSOR QUICK DISCO
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- text: 48-08-0551 FOLDING MITRE SAW STAND
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- text: JAS-LEB04-M3 COMPACT SPEED CONTROLLER
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- text: LWFS37C2R1025HS2/E37.5 RAIL
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- text: '300108'
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pipeline_tag: text-classification
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inference: false
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model-index:
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- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: Unknown
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type: unknown
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split: test
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metrics:
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- type: accuracy
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value: 0.3217244143582435
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name: Accuracy
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---
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# SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model. A OneVsRestClassifier instance is used for classification.
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The model has been trained using an efficient few-shot learning technique that involves:
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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2. Training a classification head with features from the fine-tuned Sentence Transformer.
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## Model Details
|
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### Model Description
|
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- **Model Type:** SetFit
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- **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
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- **Classification head:** a OneVsRestClassifier instance
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- **Maximum Sequence Length:** 512 tokens
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<!-- - **Number of Classes:** Unknown -->
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Model Sources
|
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- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
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- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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## Evaluation
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63 |
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### Metrics
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| Label | Accuracy |
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|:--------|:---------|
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| **all** | 0.3217 |
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## Uses
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### Direct Use for Inference
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First install the SetFit library:
|
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```bash
|
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pip install setfit
|
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```
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Then you can load this model and run inference.
|
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```python
|
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from setfit import SetFitModel
|
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# Download from the 🤗 Hub
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model = SetFitModel.from_pretrained("amitprgx/setfit-categorization")
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# Run inference
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preds = model("300108")
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```
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<!--
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### Downstream Use
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*List how someone could finetune this model on their own dataset.*
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-->
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<!--
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### Out-of-Scope Use
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*List how the model may foreseeably be misused and address what users ought not to do with the model.*
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-->
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<!--
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## Bias, Risks and Limitations
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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-->
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<!--
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### Recommendations
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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-->
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## Training Details
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### Training Set Metrics
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| Training set | Min | Median | Max |
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|:-------------|:----|:-------|:----|
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| Word count | 1 | 4.7197 | 10 |
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### Training Hyperparameters
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- batch_size: (8, 8)
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- num_epochs: (10, 10)
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- max_steps: -1
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- sampling_strategy: oversampling
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- num_iterations: 20
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- body_learning_rate: (2e-05, 2e-05)
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- head_learning_rate: 2e-05
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- loss: CosineSimilarityLoss
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- distance_metric: cosine_distance
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- margin: 0.25
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- end_to_end: False
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- use_amp: False
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- warmup_proportion: 0.1
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- seed: 42
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- eval_max_steps: -1
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- load_best_model_at_end: False
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### Training Results
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| Epoch | Step | Training Loss | Validation Loss |
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|:------:|:-----:|:-------------:|:---------------:|
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| 0.0008 | 1 | 0.1444 | - |
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| 0.0379 | 50 | 0.1563 | - |
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| 0.0758 | 100 | 0.2163 | - |
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| 0.1136 | 150 | 0.3125 | - |
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| 0.1515 | 200 | 0.2152 | - |
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| 0.1894 | 250 | 0.2731 | - |
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| 0.2273 | 300 | 0.2788 | - |
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| 0.2652 | 350 | 0.2315 | - |
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| 0.3030 | 400 | 0.1847 | - |
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| 0.3409 | 450 | 0.1253 | - |
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| 0.3788 | 500 | 0.1363 | - |
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| 0.4167 | 550 | 0.1816 | - |
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| 0.4545 | 600 | 0.1957 | - |
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| 0.4924 | 650 | 0.1931 | - |
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| 0.5303 | 700 | 0.1392 | - |
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| 0.5682 | 750 | 0.0613 | - |
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| 0.6061 | 800 | 0.0403 | - |
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| 0.6439 | 850 | 0.0796 | - |
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| 0.6818 | 900 | 0.0661 | - |
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| 0.7197 | 950 | 0.1207 | - |
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| 0.7576 | 1000 | 0.0795 | - |
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| 0.7955 | 1050 | 0.0439 | - |
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| 0.8333 | 1100 | 0.0744 | - |
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| 0.8712 | 1150 | 0.0972 | - |
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| 0.9091 | 1200 | 0.0512 | - |
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| 0.9470 | 1250 | 0.0335 | - |
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| 0.9848 | 1300 | 0.0092 | - |
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| 1.0227 | 1350 | 0.0489 | - |
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| 1.0606 | 1400 | 0.0176 | - |
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| 1.0985 | 1450 | 0.0302 | - |
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| 1.1364 | 1500 | 0.0811 | - |
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| 1.1742 | 1550 | 0.0181 | - |
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| 1.2121 | 1600 | 0.0354 | - |
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| 1.25 | 1650 | 0.0183 | - |
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| 1.2879 | 1700 | 0.0167 | - |
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| 1.3258 | 1750 | 0.006 | - |
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| 1.3636 | 1800 | 0.0294 | - |
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| 1.4015 | 1850 | 0.0342 | - |
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| 1.4394 | 1900 | 0.005 | - |
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| 1.4773 | 1950 | 0.0044 | - |
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| 1.5152 | 2000 | 0.0069 | - |
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| 1.5530 | 2050 | 0.0051 | - |
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| 1.5909 | 2100 | 0.0375 | - |
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| 1.6288 | 2150 | 0.0123 | - |
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| 1.6667 | 2200 | 0.0058 | - |
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| 1.7045 | 2250 | 0.0086 | - |
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| 1.7424 | 2300 | 0.0141 | - |
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| 1.7803 | 2350 | 0.0014 | - |
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| 1.8182 | 2400 | 0.0047 | - |
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| 1.8561 | 2450 | 0.0018 | - |
|
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| 1.8939 | 2500 | 0.0063 | - |
|
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| 1.9318 | 2550 | 0.0018 | - |
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| 1.9697 | 2600 | 0.0032 | - |
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| 2.0076 | 2650 | 0.001 | - |
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| 2.0455 | 2700 | 0.0165 | - |
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| 2.0833 | 2750 | 0.0773 | - |
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| 2.1212 | 2800 | 0.0014 | - |
|
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| 2.1591 | 2850 | 0.0105 | - |
|
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| 2.1970 | 2900 | 0.0013 | - |
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| 2.2348 | 2950 | 0.0009 | - |
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| 2.2727 | 3000 | 0.0034 | - |
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| 2.3106 | 3050 | 0.0013 | - |
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| 2.3485 | 3100 | 0.0065 | - |
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| 2.3864 | 3150 | 0.0008 | - |
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| 2.4242 | 3200 | 0.1143 | - |
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| 2.4621 | 3250 | 0.0036 | - |
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| 2.5 | 3300 | 0.0254 | - |
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| 2.5379 | 3350 | 0.0023 | - |
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| 2.5758 | 3400 | 0.004 | - |
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| 2.6136 | 3450 | 0.0034 | - |
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| 2.6515 | 3500 | 0.0019 | - |
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| 2.6894 | 3550 | 0.001 | - |
|
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| 2.7273 | 3600 | 0.1044 | - |
|
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| 2.7652 | 3650 | 0.0005 | - |
|
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| 2.8030 | 3700 | 0.0955 | - |
|
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| 2.8409 | 3750 | 0.0011 | - |
|
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| 2.8788 | 3800 | 0.0018 | - |
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| 2.9167 | 3850 | 0.0017 | - |
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| 2.9545 | 3900 | 0.0007 | - |
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| 2.9924 | 3950 | 0.001 | - |
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| 3.0303 | 4000 | 0.0009 | - |
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| 3.0682 | 4050 | 0.001 | - |
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| 3.1061 | 4100 | 0.0035 | - |
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225 |
+
| 3.1439 | 4150 | 0.0009 | - |
|
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+
| 3.1818 | 4200 | 0.0009 | - |
|
227 |
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| 3.2197 | 4250 | 0.0005 | - |
|
228 |
+
| 3.2576 | 4300 | 0.0011 | - |
|
229 |
+
| 3.2955 | 4350 | 0.0007 | - |
|
230 |
+
| 3.3333 | 4400 | 0.0007 | - |
|
231 |
+
| 3.3712 | 4450 | 0.0003 | - |
|
232 |
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| 3.4091 | 4500 | 0.0008 | - |
|
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+
| 3.4470 | 4550 | 0.0007 | - |
|
234 |
+
| 3.4848 | 4600 | 0.0004 | - |
|
235 |
+
| 3.5227 | 4650 | 0.0011 | - |
|
236 |
+
| 3.5606 | 4700 | 0.0009 | - |
|
237 |
+
| 3.5985 | 4750 | 0.0004 | - |
|
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| 3.6364 | 4800 | 0.0006 | - |
|
239 |
+
| 3.6742 | 4850 | 0.0012 | - |
|
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+
| 3.7121 | 4900 | 0.0004 | - |
|
241 |
+
| 3.75 | 4950 | 0.0003 | - |
|
242 |
+
| 3.7879 | 5000 | 0.0005 | - |
|
243 |
+
| 3.8258 | 5050 | 0.0007 | - |
|
244 |
+
| 3.8636 | 5100 | 0.0012 | - |
|
245 |
+
| 3.9015 | 5150 | 0.0003 | - |
|
246 |
+
| 3.9394 | 5200 | 0.0009 | - |
|
247 |
+
| 3.9773 | 5250 | 0.0003 | - |
|
248 |
+
| 4.0152 | 5300 | 0.0003 | - |
|
249 |
+
| 4.0530 | 5350 | 0.0005 | - |
|
250 |
+
| 4.0909 | 5400 | 0.0004 | - |
|
251 |
+
| 4.1288 | 5450 | 0.0003 | - |
|
252 |
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| 4.1667 | 5500 | 0.0003 | - |
|
253 |
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| 4.2045 | 5550 | 0.0011 | - |
|
254 |
+
| 4.2424 | 5600 | 0.0002 | - |
|
255 |
+
| 4.2803 | 5650 | 0.0004 | - |
|
256 |
+
| 4.3182 | 5700 | 0.0009 | - |
|
257 |
+
| 4.3561 | 5750 | 0.0003 | - |
|
258 |
+
| 4.3939 | 5800 | 0.0002 | - |
|
259 |
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| 4.4318 | 5850 | 0.0008 | - |
|
260 |
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| 4.4697 | 5900 | 0.0003 | - |
|
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+
| 4.5076 | 5950 | 0.0004 | - |
|
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| 4.5455 | 6000 | 0.0272 | - |
|
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+
| 4.5833 | 6050 | 0.0012 | - |
|
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+
| 4.6212 | 6100 | 0.0006 | - |
|
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| 4.6591 | 6150 | 0.0005 | - |
|
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| 4.6970 | 6200 | 0.0011 | - |
|
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| 4.7348 | 6250 | 0.0003 | - |
|
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| 4.7727 | 6300 | 0.0003 | - |
|
269 |
+
| 4.8106 | 6350 | 0.0026 | - |
|
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| 4.8485 | 6400 | 0.0007 | - |
|
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| 4.8864 | 6450 | 0.0002 | - |
|
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| 4.9242 | 6500 | 0.0007 | - |
|
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| 4.9621 | 6550 | 0.0004 | - |
|
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| 5.0 | 6600 | 0.0002 | - |
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| 5.0758 | 6700 | 0.0003 | - |
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| 5.1136 | 6750 | 0.0004 | - |
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| 5.1515 | 6800 | 0.0007 | - |
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| 5.1894 | 6850 | 0.0002 | - |
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| 5.2273 | 6900 | 0.0002 | - |
|
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| 5.2652 | 6950 | 0.0001 | - |
|
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| 5.3030 | 7000 | 0.0003 | - |
|
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| 5.3409 | 7050 | 0.0001 | - |
|
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| 5.3788 | 7100 | 0.0002 | - |
|
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| 5.4167 | 7150 | 0.0003 | - |
|
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| 5.4545 | 7200 | 0.0006 | - |
|
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| 5.4924 | 7250 | 0.0002 | - |
|
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| 5.5303 | 7300 | 0.0002 | - |
|
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| 5.5682 | 7350 | 0.0002 | - |
|
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| 5.6061 | 7400 | 0.0004 | - |
|
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| 5.6439 | 7450 | 0.0003 | - |
|
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| 5.6818 | 7500 | 0.0002 | - |
|
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| 5.7197 | 7550 | 0.0002 | - |
|
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| 5.7576 | 7600 | 0.0002 | - |
|
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+
| 5.7955 | 7650 | 0.0005 | - |
|
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+
| 5.8333 | 7700 | 0.0013 | - |
|
297 |
+
| 5.8712 | 7750 | 0.0002 | - |
|
298 |
+
| 5.9091 | 7800 | 0.0015 | - |
|
299 |
+
| 5.9470 | 7850 | 0.0001 | - |
|
300 |
+
| 5.9848 | 7900 | 0.0002 | - |
|
301 |
+
| 6.0227 | 7950 | 0.0001 | - |
|
302 |
+
| 6.0606 | 8000 | 0.0015 | - |
|
303 |
+
| 6.0985 | 8050 | 0.0004 | - |
|
304 |
+
| 6.1364 | 8100 | 0.0373 | - |
|
305 |
+
| 6.1742 | 8150 | 0.0003 | - |
|
306 |
+
| 6.2121 | 8200 | 0.0002 | - |
|
307 |
+
| 6.25 | 8250 | 0.0003 | - |
|
308 |
+
| 6.2879 | 8300 | 0.0003 | - |
|
309 |
+
| 6.3258 | 8350 | 0.0003 | - |
|
310 |
+
| 6.3636 | 8400 | 0.0002 | - |
|
311 |
+
| 6.4015 | 8450 | 0.0001 | - |
|
312 |
+
| 6.4394 | 8500 | 0.0004 | - |
|
313 |
+
| 6.4773 | 8550 | 0.0002 | - |
|
314 |
+
| 6.5152 | 8600 | 0.0002 | - |
|
315 |
+
| 6.5530 | 8650 | 0.0002 | - |
|
316 |
+
| 6.5909 | 8700 | 0.0004 | - |
|
317 |
+
| 6.6288 | 8750 | 0.0002 | - |
|
318 |
+
| 6.6667 | 8800 | 0.0001 | - |
|
319 |
+
| 6.7045 | 8850 | 0.0003 | - |
|
320 |
+
| 6.7424 | 8900 | 0.0001 | - |
|
321 |
+
| 6.7803 | 8950 | 0.0002 | - |
|
322 |
+
| 6.8182 | 9000 | 0.0003 | - |
|
323 |
+
| 6.8561 | 9050 | 0.0002 | - |
|
324 |
+
| 6.8939 | 9100 | 0.0002 | - |
|
325 |
+
| 6.9318 | 9150 | 0.0001 | - |
|
326 |
+
| 6.9697 | 9200 | 0.0001 | - |
|
327 |
+
| 7.0076 | 9250 | 0.0002 | - |
|
328 |
+
| 7.0455 | 9300 | 0.0002 | - |
|
329 |
+
| 7.0833 | 9350 | 0.0002 | - |
|
330 |
+
| 7.1212 | 9400 | 0.0001 | - |
|
331 |
+
| 7.1591 | 9450 | 0.0002 | - |
|
332 |
+
| 7.1970 | 9500 | 0.0003 | - |
|
333 |
+
| 7.2348 | 9550 | 0.0005 | - |
|
334 |
+
| 7.2727 | 9600 | 0.0002 | - |
|
335 |
+
| 7.3106 | 9650 | 0.0002 | - |
|
336 |
+
| 7.3485 | 9700 | 0.0002 | - |
|
337 |
+
| 7.3864 | 9750 | 0.0002 | - |
|
338 |
+
| 7.4242 | 9800 | 0.0002 | - |
|
339 |
+
| 7.4621 | 9850 | 0.0001 | - |
|
340 |
+
| 7.5 | 9900 | 0.0001 | - |
|
341 |
+
| 7.5379 | 9950 | 0.0002 | - |
|
342 |
+
| 7.5758 | 10000 | 0.0001 | - |
|
343 |
+
| 7.6136 | 10050 | 0.0001 | - |
|
344 |
+
| 7.6515 | 10100 | 0.0001 | - |
|
345 |
+
| 7.6894 | 10150 | 0.0002 | - |
|
346 |
+
| 7.7273 | 10200 | 0.0002 | - |
|
347 |
+
| 7.7652 | 10250 | 0.0001 | - |
|
348 |
+
| 7.8030 | 10300 | 0.0002 | - |
|
349 |
+
| 7.8409 | 10350 | 0.0003 | - |
|
350 |
+
| 7.8788 | 10400 | 0.0002 | - |
|
351 |
+
| 7.9167 | 10450 | 0.0002 | - |
|
352 |
+
| 7.9545 | 10500 | 0.0001 | - |
|
353 |
+
| 7.9924 | 10550 | 0.0002 | - |
|
354 |
+
| 8.0303 | 10600 | 0.0002 | - |
|
355 |
+
| 8.0682 | 10650 | 0.0002 | - |
|
356 |
+
| 8.1061 | 10700 | 0.0002 | - |
|
357 |
+
| 8.1439 | 10750 | 0.0001 | - |
|
358 |
+
| 8.1818 | 10800 | 0.0001 | - |
|
359 |
+
| 8.2197 | 10850 | 0.0001 | - |
|
360 |
+
| 8.2576 | 10900 | 0.0001 | - |
|
361 |
+
| 8.2955 | 10950 | 0.0001 | - |
|
362 |
+
| 8.3333 | 11000 | 0.0002 | - |
|
363 |
+
| 8.3712 | 11050 | 0.0007 | - |
|
364 |
+
| 8.4091 | 11100 | 0.0001 | - |
|
365 |
+
| 8.4470 | 11150 | 0.0002 | - |
|
366 |
+
| 8.4848 | 11200 | 0.0001 | - |
|
367 |
+
| 8.5227 | 11250 | 0.0002 | - |
|
368 |
+
| 8.5606 | 11300 | 0.0001 | - |
|
369 |
+
| 8.5985 | 11350 | 0.0001 | - |
|
370 |
+
| 8.6364 | 11400 | 0.0001 | - |
|
371 |
+
| 8.6742 | 11450 | 0.0001 | - |
|
372 |
+
| 8.7121 | 11500 | 0.0002 | - |
|
373 |
+
| 8.75 | 11550 | 0.0001 | - |
|
374 |
+
| 8.7879 | 11600 | 0.0001 | - |
|
375 |
+
| 8.8258 | 11650 | 0.0001 | - |
|
376 |
+
| 8.8636 | 11700 | 0.0001 | - |
|
377 |
+
| 8.9015 | 11750 | 0.0001 | - |
|
378 |
+
| 8.9394 | 11800 | 0.0001 | - |
|
379 |
+
| 8.9773 | 11850 | 0.0001 | - |
|
380 |
+
| 9.0152 | 11900 | 0.0001 | - |
|
381 |
+
| 9.0530 | 11950 | 0.0001 | - |
|
382 |
+
| 9.0909 | 12000 | 0.0001 | - |
|
383 |
+
| 9.1288 | 12050 | 0.0001 | - |
|
384 |
+
| 9.1667 | 12100 | 0.0002 | - |
|
385 |
+
| 9.2045 | 12150 | 0.0001 | - |
|
386 |
+
| 9.2424 | 12200 | 0.0001 | - |
|
387 |
+
| 9.2803 | 12250 | 0.0002 | - |
|
388 |
+
| 9.3182 | 12300 | 0.0002 | - |
|
389 |
+
| 9.3561 | 12350 | 0.0002 | - |
|
390 |
+
| 9.3939 | 12400 | 0.0001 | - |
|
391 |
+
| 9.4318 | 12450 | 0.0003 | - |
|
392 |
+
| 9.4697 | 12500 | 0.0001 | - |
|
393 |
+
| 9.5076 | 12550 | 0.0001 | - |
|
394 |
+
| 9.5455 | 12600 | 0.0001 | - |
|
395 |
+
| 9.5833 | 12650 | 0.0002 | - |
|
396 |
+
| 9.6212 | 12700 | 0.0001 | - |
|
397 |
+
| 9.6591 | 12750 | 0.0002 | - |
|
398 |
+
| 9.6970 | 12800 | 0.0002 | - |
|
399 |
+
| 9.7348 | 12850 | 0.0001 | - |
|
400 |
+
| 9.7727 | 12900 | 0.0001 | - |
|
401 |
+
| 9.8106 | 12950 | 0.0001 | - |
|
402 |
+
| 9.8485 | 13000 | 0.0001 | - |
|
403 |
+
| 9.8864 | 13050 | 0.0001 | - |
|
404 |
+
| 9.9242 | 13100 | 0.0001 | - |
|
405 |
+
| 9.9621 | 13150 | 0.0001 | - |
|
406 |
+
| 10.0 | 13200 | 0.0002 | - |
|
407 |
+
|
408 |
+
### Framework Versions
|
409 |
+
- Python: 3.11.8
|
410 |
+
- SetFit: 1.1.0.dev0
|
411 |
+
- Sentence Transformers: 2.6.1
|
412 |
+
- Transformers: 4.39.3
|
413 |
+
- PyTorch: 1.13.1+cu117
|
414 |
+
- Datasets: 2.19.0
|
415 |
+
- Tokenizers: 0.15.2
|
416 |
+
|
417 |
+
## Citation
|
418 |
+
|
419 |
+
### BibTeX
|
420 |
+
```bibtex
|
421 |
+
@article{https://doi.org/10.48550/arxiv.2209.11055,
|
422 |
+
doi = {10.48550/ARXIV.2209.11055},
|
423 |
+
url = {https://arxiv.org/abs/2209.11055},
|
424 |
+
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
|
425 |
+
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
|
426 |
+
title = {Efficient Few-Shot Learning Without Prompts},
|
427 |
+
publisher = {arXiv},
|
428 |
+
year = {2022},
|
429 |
+
copyright = {Creative Commons Attribution 4.0 International}
|
430 |
+
}
|
431 |
+
```
|
432 |
+
|
433 |
+
<!--
|
434 |
+
## Glossary
|
435 |
+
|
436 |
+
*Clearly define terms in order to be accessible across audiences.*
|
437 |
+
-->
|
438 |
+
|
439 |
+
<!--
|
440 |
+
## Model Card Authors
|
441 |
+
|
442 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
443 |
+
-->
|
444 |
+
|
445 |
+
<!--
|
446 |
+
## Model Card Contact
|
447 |
+
|
448 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
449 |
+
-->
|
config.json
ADDED
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "sentence-transformers/paraphrase-mpnet-base-v2",
|
3 |
+
"architectures": [
|
4 |
+
"MPNetModel"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.1,
|
7 |
+
"bos_token_id": 0,
|
8 |
+
"eos_token_id": 2,
|
9 |
+
"hidden_act": "gelu",
|
10 |
+
"hidden_dropout_prob": 0.1,
|
11 |
+
"hidden_size": 768,
|
12 |
+
"initializer_range": 0.02,
|
13 |
+
"intermediate_size": 3072,
|
14 |
+
"layer_norm_eps": 1e-05,
|
15 |
+
"max_position_embeddings": 514,
|
16 |
+
"model_type": "mpnet",
|
17 |
+
"num_attention_heads": 12,
|
18 |
+
"num_hidden_layers": 12,
|
19 |
+
"pad_token_id": 1,
|
20 |
+
"relative_attention_num_buckets": 32,
|
21 |
+
"torch_dtype": "float32",
|
22 |
+
"transformers_version": "4.39.3",
|
23 |
+
"vocab_size": 30527
|
24 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "2.0.0",
|
4 |
+
"transformers": "4.7.0",
|
5 |
+
"pytorch": "1.9.0+cu102"
|
6 |
+
},
|
7 |
+
"prompts": {},
|
8 |
+
"default_prompt_name": null
|
9 |
+
}
|
config_setfit.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"normalize_embeddings": false,
|
3 |
+
"labels": null
|
4 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:468f98b1e5b3ba7e2c3d6c228915536191946c308a9746f122e454d532ffb162
|
3 |
+
size 437967672
|
model_head.pkl
ADDED
@@ -0,0 +1,3 @@
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|
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|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3d602f4ba884361f2ed14170468d13e2a3cb8f67bbf0a3f0e6a39eb7381ab9c1
|
3 |
+
size 214836
|
modules.json
ADDED
@@ -0,0 +1,14 @@
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"idx": 0,
|
4 |
+
"name": "0",
|
5 |
+
"path": "",
|
6 |
+
"type": "sentence_transformers.models.Transformer"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"idx": 1,
|
10 |
+
"name": "1",
|
11 |
+
"path": "1_Pooling",
|
12 |
+
"type": "sentence_transformers.models.Pooling"
|
13 |
+
}
|
14 |
+
]
|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"max_seq_length": 512,
|
3 |
+
"do_lower_case": false
|
4 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,51 @@
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|
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|
1 |
+
{
|
2 |
+
"bos_token": {
|
3 |
+
"content": "<s>",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": false,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"cls_token": {
|
10 |
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"content": "<s>",
|
11 |
+
"lstrip": false,
|
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|
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"rstrip": false,
|
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"single_word": false
|
15 |
+
},
|
16 |
+
"eos_token": {
|
17 |
+
"content": "</s>",
|
18 |
+
"lstrip": false,
|
19 |
+
"normalized": false,
|
20 |
+
"rstrip": false,
|
21 |
+
"single_word": false
|
22 |
+
},
|
23 |
+
"mask_token": {
|
24 |
+
"content": "<mask>",
|
25 |
+
"lstrip": true,
|
26 |
+
"normalized": false,
|
27 |
+
"rstrip": false,
|
28 |
+
"single_word": false
|
29 |
+
},
|
30 |
+
"pad_token": {
|
31 |
+
"content": "<pad>",
|
32 |
+
"lstrip": false,
|
33 |
+
"normalized": false,
|
34 |
+
"rstrip": false,
|
35 |
+
"single_word": false
|
36 |
+
},
|
37 |
+
"sep_token": {
|
38 |
+
"content": "</s>",
|
39 |
+
"lstrip": false,
|
40 |
+
"normalized": false,
|
41 |
+
"rstrip": false,
|
42 |
+
"single_word": false
|
43 |
+
},
|
44 |
+
"unk_token": {
|
45 |
+
"content": "[UNK]",
|
46 |
+
"lstrip": false,
|
47 |
+
"normalized": false,
|
48 |
+
"rstrip": false,
|
49 |
+
"single_word": false
|
50 |
+
}
|
51 |
+
}
|
tokenizer.json
ADDED
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|
tokenizer_config.json
ADDED
@@ -0,0 +1,59 @@
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|
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|
|
|
1 |
+
{
|
2 |
+
"added_tokens_decoder": {
|
3 |
+
"0": {
|
4 |
+
"content": "<s>",
|
5 |
+
"lstrip": false,
|
6 |
+
"normalized": false,
|
7 |
+
"rstrip": false,
|
8 |
+
"single_word": false,
|
9 |
+
"special": true
|
10 |
+
},
|
11 |
+
"1": {
|
12 |
+
"content": "<pad>",
|
13 |
+
"lstrip": false,
|
14 |
+
"normalized": false,
|
15 |
+
"rstrip": false,
|
16 |
+
"single_word": false,
|
17 |
+
"special": true
|
18 |
+
},
|
19 |
+
"2": {
|
20 |
+
"content": "</s>",
|
21 |
+
"lstrip": false,
|
22 |
+
"normalized": false,
|
23 |
+
"rstrip": false,
|
24 |
+
"single_word": false,
|
25 |
+
"special": true
|
26 |
+
},
|
27 |
+
"104": {
|
28 |
+
"content": "[UNK]",
|
29 |
+
"lstrip": false,
|
30 |
+
"normalized": false,
|
31 |
+
"rstrip": false,
|
32 |
+
"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
+
"30526": {
|
36 |
+
"content": "<mask>",
|
37 |
+
"lstrip": true,
|
38 |
+
"normalized": false,
|
39 |
+
"rstrip": false,
|
40 |
+
"single_word": false,
|
41 |
+
"special": true
|
42 |
+
}
|
43 |
+
},
|
44 |
+
"bos_token": "<s>",
|
45 |
+
"clean_up_tokenization_spaces": true,
|
46 |
+
"cls_token": "<s>",
|
47 |
+
"do_basic_tokenize": true,
|
48 |
+
"do_lower_case": true,
|
49 |
+
"eos_token": "</s>",
|
50 |
+
"mask_token": "<mask>",
|
51 |
+
"model_max_length": 512,
|
52 |
+
"never_split": null,
|
53 |
+
"pad_token": "<pad>",
|
54 |
+
"sep_token": "</s>",
|
55 |
+
"strip_accents": null,
|
56 |
+
"tokenize_chinese_chars": true,
|
57 |
+
"tokenizer_class": "MPNetTokenizer",
|
58 |
+
"unk_token": "[UNK]"
|
59 |
+
}
|
vocab.txt
ADDED
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|