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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-NON-KD-SCR-COPY-CDF-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-NON-KD-SCR-COPY-CDF-EN-D2_data-en-cardiff_eng_only44 |
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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: 5.7960 |
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- Accuracy: 0.3448 |
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- F1: 0.3121 |
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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 | 1.1461 | 0.3593 | 0.3245 | |
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| No log | 3.45 | 200 | 1.9614 | 0.3611 | 0.3512 | |
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| No log | 5.17 | 300 | 2.6180 | 0.3492 | 0.3157 | |
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| No log | 6.9 | 400 | 3.1787 | 0.3673 | 0.3633 | |
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| 0.4792 | 8.62 | 500 | 3.7077 | 0.3527 | 0.3312 | |
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| 0.4792 | 10.34 | 600 | 4.5969 | 0.3549 | 0.3296 | |
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| 0.4792 | 12.07 | 700 | 4.8433 | 0.3483 | 0.3159 | |
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| 0.4792 | 13.79 | 800 | 5.1229 | 0.3602 | 0.3462 | |
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| 0.4792 | 15.52 | 900 | 5.3356 | 0.3554 | 0.3354 | |
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| 0.0195 | 17.24 | 1000 | 5.5333 | 0.3567 | 0.3421 | |
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| 0.0195 | 18.97 | 1100 | 5.4819 | 0.3660 | 0.3534 | |
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| 0.0195 | 20.69 | 1200 | 5.6908 | 0.3607 | 0.3366 | |
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| 0.0195 | 22.41 | 1300 | 5.7411 | 0.3483 | 0.3192 | |
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| 0.0195 | 24.14 | 1400 | 5.7830 | 0.3501 | 0.3217 | |
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| 0.0081 | 25.86 | 1500 | 5.8334 | 0.3457 | 0.3113 | |
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| 0.0081 | 27.59 | 1600 | 5.7030 | 0.3532 | 0.3299 | |
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| 0.0081 | 29.31 | 1700 | 5.7960 | 0.3448 | 0.3121 | |
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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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