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--- |
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license: mit |
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base_model: FacebookAI/xlm-roberta-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-KD-PR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only_gamma-jason |
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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-CL-D2_data-en-cardiff_eng_only_gamma-jason |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 16.3831 |
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- Accuracy: 0.3955 |
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- F1: 0.3889 |
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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: 88458 |
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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 | 12.6768 | 0.3280 | 0.2299 | |
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| No log | 3.45 | 200 | 12.6987 | 0.3836 | 0.3671 | |
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| No log | 5.17 | 300 | 12.8320 | 0.3858 | 0.3602 | |
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| No log | 6.9 | 400 | 13.1201 | 0.3620 | 0.3230 | |
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| 13.3889 | 8.62 | 500 | 13.0591 | 0.3920 | 0.3845 | |
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| 13.3889 | 10.34 | 600 | 14.1639 | 0.4004 | 0.3832 | |
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| 13.3889 | 12.07 | 700 | 14.7159 | 0.3810 | 0.3536 | |
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| 13.3889 | 13.79 | 800 | 14.3341 | 0.3907 | 0.3815 | |
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| 13.3889 | 15.52 | 900 | 14.9958 | 0.3792 | 0.3564 | |
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| 9.5405 | 17.24 | 1000 | 14.4299 | 0.3902 | 0.3887 | |
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| 9.5405 | 18.97 | 1100 | 15.3658 | 0.3999 | 0.3973 | |
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| 9.5405 | 20.69 | 1200 | 15.1707 | 0.3990 | 0.3940 | |
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| 9.5405 | 22.41 | 1300 | 15.8556 | 0.3955 | 0.3816 | |
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| 9.5405 | 24.14 | 1400 | 15.7963 | 0.3915 | 0.3825 | |
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| 6.9987 | 25.86 | 1500 | 15.8559 | 0.4056 | 0.4012 | |
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| 6.9987 | 27.59 | 1600 | 16.1802 | 0.3854 | 0.3757 | |
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| 6.9987 | 29.31 | 1700 | 16.3831 | 0.3955 | 0.3889 | |
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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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