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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_beta-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_beta-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: 15.8985 |
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- Accuracy: 0.4109 |
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- F1: 0.4052 |
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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: 6666 |
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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 | 12.7770 | 0.3289 | 0.2140 | |
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| No log | 3.45 | 200 | 12.5133 | 0.3611 | 0.3597 | |
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| No log | 5.17 | 300 | 12.8380 | 0.3854 | 0.3580 | |
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| No log | 6.9 | 400 | 12.8508 | 0.4061 | 0.4051 | |
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| 13.1287 | 8.62 | 500 | 13.5318 | 0.4017 | 0.3945 | |
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| 13.1287 | 10.34 | 600 | 13.1743 | 0.3973 | 0.3971 | |
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| 13.1287 | 12.07 | 700 | 13.8236 | 0.4114 | 0.4114 | |
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| 13.1287 | 13.79 | 800 | 14.0940 | 0.3854 | 0.3717 | |
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| 13.1287 | 15.52 | 900 | 14.3671 | 0.4008 | 0.3905 | |
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| 9.0164 | 17.24 | 1000 | 14.6749 | 0.4078 | 0.3961 | |
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| 9.0164 | 18.97 | 1100 | 14.8097 | 0.3924 | 0.3850 | |
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| 9.0164 | 20.69 | 1200 | 15.4684 | 0.3867 | 0.3827 | |
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| 9.0164 | 22.41 | 1300 | 15.2537 | 0.4078 | 0.4008 | |
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| 9.0164 | 24.14 | 1400 | 16.0142 | 0.4039 | 0.3995 | |
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| 6.3951 | 25.86 | 1500 | 15.7916 | 0.4105 | 0.4106 | |
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| 6.3951 | 27.59 | 1600 | 16.2415 | 0.3827 | 0.3681 | |
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| 6.3951 | 29.31 | 1700 | 15.8985 | 0.4109 | 0.4052 | |
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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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