Model save
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- model.safetensors +1 -1
README.md
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---
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license: mit
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base_model: microsoft/deberta-v3-base
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: deberta-v3-base-orgs-v1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# deberta-v3-base-orgs-v1
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1186
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- Precision: 0.8127
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- Recall: 0.7735
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- F1: 0.7927
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- Accuracy: 0.9632
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 128
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- eval_batch_size: 256
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.0706 | 0.7 | 600 | 0.1138 | 0.7590 | 0.7793 | 0.7690 | 0.9602 |
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| 0.0526 | 1.4 | 1200 | 0.1113 | 0.7942 | 0.7799 | 0.7870 | 0.9617 |
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| 0.0409 | 2.11 | 1800 | 0.1125 | 0.7911 | 0.7839 | 0.7875 | 0.9627 |
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| 0.0376 | 2.81 | 2400 | 0.1186 | 0.8127 | 0.7735 | 0.7927 | 0.9632 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0a0+32f93b1
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 735359804
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version https://git-lfs.github.com/spec/v1
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size 735359804
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