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--- |
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license: mit |
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base_model: microsoft/mdeberta-v3-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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model-index: |
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- name: scenario-MDBT-TCR_data-cl-cardiff_cl_only |
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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-MDBT-TCR_data-cl-cardiff_cl_only |
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This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.6543 |
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- Accuracy: 0.5131 |
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- F1: 0.5145 |
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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: 64 |
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- eval_batch_size: 128 |
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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 | 2.17 | 250 | 1.4134 | 0.5069 | 0.5083 | |
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| 0.5524 | 4.35 | 500 | 1.9853 | 0.5208 | 0.5230 | |
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| 0.5524 | 6.52 | 750 | 2.5990 | 0.4853 | 0.4797 | |
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| 0.1315 | 8.7 | 1000 | 2.8603 | 0.4961 | 0.4954 | |
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| 0.1315 | 10.87 | 1250 | 3.1408 | 0.5093 | 0.5099 | |
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| 0.0497 | 13.04 | 1500 | 3.3859 | 0.5177 | 0.5190 | |
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| 0.0497 | 15.22 | 1750 | 3.9204 | 0.5039 | 0.5044 | |
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| 0.0219 | 17.39 | 2000 | 4.0747 | 0.5139 | 0.5160 | |
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| 0.0219 | 19.57 | 2250 | 4.3170 | 0.5139 | 0.5156 | |
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| 0.0133 | 21.74 | 2500 | 4.5924 | 0.5023 | 0.5020 | |
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| 0.0133 | 23.91 | 2750 | 4.6042 | 0.5100 | 0.5114 | |
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| 0.0046 | 26.09 | 3000 | 4.5407 | 0.5147 | 0.5163 | |
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| 0.0046 | 28.26 | 3250 | 4.6543 | 0.5131 | 0.5145 | |
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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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