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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/deberta-v3-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: deberta-v3-small-Label_B-768-epochs-5 |
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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-small-Label_B-768-epochs-5 |
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0703 |
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- Accuracy: 0.9868 |
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- F1: 0.9868 |
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- Precision: 0.9869 |
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- Recall: 0.9868 |
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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: 5e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 48 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.0851 | 0.9995 | 1066 | 0.0843 | 0.9747 | 0.9746 | 0.9752 | 0.9747 | |
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| 0.0433 | 2.0 | 2133 | 0.0894 | 0.9755 | 0.9755 | 0.9764 | 0.9755 | |
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| 0.0251 | 2.9995 | 3199 | 0.0651 | 0.9829 | 0.9829 | 0.9831 | 0.9829 | |
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| 0.0025 | 4.0 | 4266 | 0.0703 | 0.9868 | 0.9868 | 0.9869 | 0.9868 | |
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| 0.0035 | 4.9977 | 5330 | 0.0996 | 0.9819 | 0.9820 | 0.9824 | 0.9819 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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