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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/bigbird-roberta-base |
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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: jackmedda/google-bigbird-roberta-base_finetuned_augmented_augmented_deepseek |
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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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# jackmedda/google-bigbird-roberta-base_finetuned_augmented_augmented_deepseek |
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This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3040 |
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- Accuracy: 0.7647 |
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- F1: 0.8571 |
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- Precision: 0.8 |
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- Recall: 0.9231 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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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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| 0.4568 | 1.0 | 46 | 0.7344 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.6053 | 2.0 | 92 | 0.6889 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.5004 | 3.0 | 138 | 0.6289 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.6076 | 4.0 | 184 | 0.6493 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.3798 | 5.0 | 230 | 0.7945 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.2401 | 6.0 | 276 | 1.2776 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.4076 | 7.0 | 322 | 1.1325 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.1193 | 8.0 | 368 | 1.1424 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.3332 | 9.0 | 414 | 0.9214 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.1445 | 10.0 | 460 | 0.2424 | 0.9 | 0.9333 | 0.875 | 1.0 | |
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| 0.0029 | 11.0 | 506 | 1.6181 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.1174 | 12.0 | 552 | 0.0031 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0014 | 13.0 | 598 | 1.2314 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.0011 | 14.0 | 644 | 1.1105 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.0008 | 15.0 | 690 | 1.2286 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.0008 | 16.0 | 736 | 1.2704 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.0006 | 17.0 | 782 | 1.3157 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.0005 | 18.0 | 828 | 1.3290 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.0005 | 19.0 | 874 | 1.3752 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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| 0.0004 | 20.0 | 920 | 1.3951 | 0.8 | 0.875 | 0.7778 | 1.0 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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