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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_only44 |
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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_only44 |
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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: 1.3472 |
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- Accuracy: 0.4854 |
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- F1: 0.4837 |
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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: 44 |
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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 | 1.2889 | 0.4594 | 0.4362 | |
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| No log | 3.45 | 200 | 1.2863 | 0.4802 | 0.4774 | |
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| No log | 5.17 | 300 | 1.3275 | 0.4612 | 0.4493 | |
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| No log | 6.9 | 400 | 1.3428 | 0.4885 | 0.4874 | |
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| 1.1183 | 8.62 | 500 | 1.3395 | 0.4841 | 0.4835 | |
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| 1.1183 | 10.34 | 600 | 1.3621 | 0.4705 | 0.4689 | |
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| 1.1183 | 12.07 | 700 | 1.3524 | 0.4643 | 0.4624 | |
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| 1.1183 | 13.79 | 800 | 1.3665 | 0.4660 | 0.4617 | |
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| 1.1183 | 15.52 | 900 | 1.3531 | 0.4793 | 0.4762 | |
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| 0.9576 | 17.24 | 1000 | 1.3762 | 0.4669 | 0.4633 | |
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| 0.9576 | 18.97 | 1100 | 1.3615 | 0.4718 | 0.4681 | |
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| 0.9576 | 20.69 | 1200 | 1.3656 | 0.4691 | 0.4638 | |
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| 0.9576 | 22.41 | 1300 | 1.3684 | 0.4722 | 0.4685 | |
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| 0.9576 | 24.14 | 1400 | 1.3559 | 0.4740 | 0.4741 | |
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| 0.9369 | 25.86 | 1500 | 1.3527 | 0.4753 | 0.4739 | |
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| 0.9369 | 27.59 | 1600 | 1.3407 | 0.4762 | 0.4757 | |
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| 0.9369 | 29.31 | 1700 | 1.3472 | 0.4854 | 0.4837 | |
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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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