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--- |
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license: mit |
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base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only |
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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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model-index: |
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- name: scenario-KD-PR-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only66 |
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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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# scenario-KD-PR-CDF-EN-FROM-EN-D2_data-en-cardiff_eng_only66 |
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This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3348 |
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- Accuracy: 0.4846 |
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- F1: 0.4848 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 66 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| No log | 1.72 | 100 | 1.3126 | 0.4718 | 0.4615 | |
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| No log | 3.45 | 200 | 1.3334 | 0.4638 | 0.4466 | |
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| No log | 5.17 | 300 | 1.3417 | 0.4810 | 0.4818 | |
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| No log | 6.9 | 400 | 1.3541 | 0.4766 | 0.4702 | |
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| 1.1194 | 8.62 | 500 | 1.3613 | 0.4916 | 0.4913 | |
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| 1.1194 | 10.34 | 600 | 1.3438 | 0.4797 | 0.4784 | |
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| 1.1194 | 12.07 | 700 | 1.3501 | 0.4713 | 0.4713 | |
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| 1.1194 | 13.79 | 800 | 1.3617 | 0.4687 | 0.4683 | |
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| 1.1194 | 15.52 | 900 | 1.3527 | 0.4819 | 0.4812 | |
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| 0.9567 | 17.24 | 1000 | 1.3561 | 0.4824 | 0.4777 | |
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| 0.9567 | 18.97 | 1100 | 1.3531 | 0.4749 | 0.4732 | |
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| 0.9567 | 20.69 | 1200 | 1.3379 | 0.4960 | 0.4965 | |
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| 0.9567 | 22.41 | 1300 | 1.3384 | 0.4797 | 0.4793 | |
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| 0.9567 | 24.14 | 1400 | 1.3404 | 0.4824 | 0.4807 | |
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| 0.9355 | 25.86 | 1500 | 1.3475 | 0.4753 | 0.4755 | |
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| 0.9355 | 27.59 | 1600 | 1.3409 | 0.4780 | 0.4776 | |
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| 0.9355 | 29.31 | 1700 | 1.3348 | 0.4846 | 0.4848 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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