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--- |
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base_model: microsoft/mdeberta-v3-base |
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library_name: transformers |
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license: mit |
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metrics: |
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- accuracy |
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- f1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: scenario-NON-KD-PR-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-PR-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: 5.1657 |
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- Accuracy: 0.4577 |
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- F1: 0.4543 |
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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 | 1.7241 | 100 | 1.1068 | 0.4330 | 0.3826 | |
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| No log | 3.4483 | 200 | 1.4495 | 0.4533 | 0.4238 | |
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| No log | 5.1724 | 300 | 1.5295 | 0.4586 | 0.4497 | |
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| No log | 6.8966 | 400 | 2.0122 | 0.4537 | 0.4516 | |
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| 0.5768 | 8.6207 | 500 | 3.0885 | 0.4493 | 0.4417 | |
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| 0.5768 | 10.3448 | 600 | 3.3878 | 0.4541 | 0.4497 | |
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| 0.5768 | 12.0690 | 700 | 3.4115 | 0.4586 | 0.4564 | |
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| 0.5768 | 13.7931 | 800 | 3.8779 | 0.4590 | 0.4572 | |
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| 0.5768 | 15.5172 | 900 | 4.1514 | 0.4590 | 0.4579 | |
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| 0.0737 | 17.2414 | 1000 | 4.6699 | 0.4462 | 0.4281 | |
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| 0.0737 | 18.9655 | 1100 | 4.6724 | 0.4608 | 0.4612 | |
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| 0.0737 | 20.6897 | 1200 | 4.6790 | 0.4603 | 0.4562 | |
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| 0.0737 | 22.4138 | 1300 | 4.9305 | 0.4581 | 0.4564 | |
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| 0.0737 | 24.1379 | 1400 | 5.0621 | 0.4568 | 0.4503 | |
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| 0.0099 | 25.8621 | 1500 | 5.0787 | 0.4608 | 0.4574 | |
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| 0.0099 | 27.5862 | 1600 | 5.1428 | 0.4581 | 0.4549 | |
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| 0.0099 | 29.3103 | 1700 | 5.1657 | 0.4577 | 0.4543 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.19.1 |
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