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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_only55 |
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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_only55 |
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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: 1.3581 |
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- Accuracy: 0.4652 |
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- F1: 0.4628 |
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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: 55 |
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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 | 1.3031 | 0.4771 | 0.4716 | |
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| No log | 3.45 | 200 | 1.3400 | 0.4683 | 0.4652 | |
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| No log | 5.17 | 300 | 1.3825 | 0.4519 | 0.4469 | |
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| No log | 6.9 | 400 | 1.3630 | 0.4506 | 0.4420 | |
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| 1.1126 | 8.62 | 500 | 1.3707 | 0.4638 | 0.4582 | |
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| 1.1126 | 10.34 | 600 | 1.3829 | 0.4586 | 0.4484 | |
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| 1.1126 | 12.07 | 700 | 1.3900 | 0.4515 | 0.4453 | |
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| 1.1126 | 13.79 | 800 | 1.3686 | 0.4533 | 0.4524 | |
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| 1.1126 | 15.52 | 900 | 1.3663 | 0.4691 | 0.4671 | |
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| 0.9617 | 17.24 | 1000 | 1.3568 | 0.4634 | 0.4633 | |
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| 0.9617 | 18.97 | 1100 | 1.3790 | 0.4687 | 0.4636 | |
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| 0.9617 | 20.69 | 1200 | 1.3537 | 0.4744 | 0.4719 | |
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| 0.9617 | 22.41 | 1300 | 1.3759 | 0.4735 | 0.4682 | |
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| 0.9617 | 24.14 | 1400 | 1.3573 | 0.4687 | 0.4675 | |
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| 0.9417 | 25.86 | 1500 | 1.3581 | 0.4740 | 0.4734 | |
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| 0.9417 | 27.59 | 1600 | 1.3547 | 0.4608 | 0.4588 | |
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| 0.9417 | 29.31 | 1700 | 1.3581 | 0.4652 | 0.4628 | |
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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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