license: apache-2.0 | |
tags: | |
- generated_from_trainer | |
metrics: | |
- f1 | |
- accuracy | |
- precision | |
- recall | |
base_model: distilbert-base-uncased-finetuned-sst-2-english | |
model-index: | |
- name: soft-search | |
results: [] | |
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should probably proofread and complete it, then remove this comment. --> | |
# soft-search | |
This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.5558 | |
- F1: 0.5960 | |
- Accuracy: 0.7109 | |
- Precision: 0.5769 | |
- Recall: 0.6164 | |
## Model description | |
More information needed | |
## Intended uses & limitations | |
More information needed | |
## Training and evaluation data | |
More information needed | |
## Training procedure | |
### Training hyperparameters | |
The following hyperparameters were used during training: | |
- learning_rate: 3e-05 | |
- train_batch_size: 12 | |
- eval_batch_size: 12 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 5 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | | |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:| | |
| 0.5939 | 1.0 | 71 | 0.5989 | 0.0533 | 0.6635 | 1.0 | 0.0274 | | |
| 0.5903 | 2.0 | 142 | 0.5558 | 0.5960 | 0.7109 | 0.5769 | 0.6164 | | |
| 0.4613 | 3.0 | 213 | 0.6670 | 0.5641 | 0.6777 | 0.5301 | 0.6027 | | |
| 0.4454 | 4.0 | 284 | 0.7647 | 0.5541 | 0.6872 | 0.5467 | 0.5616 | | |
| 0.2931 | 5.0 | 355 | 0.8726 | 0.5139 | 0.6682 | 0.5211 | 0.5068 | | |
### Framework versions | |
- Transformers 4.25.1 | |
- Pytorch 1.13.1+cu117 | |
- Datasets 2.8.0 | |
- Tokenizers 0.13.2 | |