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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-EN-D2_data-en-cardiff_eng_only_delta-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-EN-D2_data-en-cardiff_eng_only_delta-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: 25.8673 |
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- Accuracy: 0.3959 |
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- F1: 0.3838 |
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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: 7777 |
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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 | 21.4869 | 0.3399 | 0.2229 | |
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| No log | 3.45 | 200 | 21.6387 | 0.3699 | 0.3103 | |
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| No log | 5.17 | 300 | 21.3511 | 0.3907 | 0.3762 | |
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| No log | 6.9 | 400 | 21.9513 | 0.3968 | 0.3590 | |
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| 22.0328 | 8.62 | 500 | 21.5760 | 0.4048 | 0.3925 | |
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| 22.0328 | 10.34 | 600 | 21.8280 | 0.4259 | 0.4236 | |
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| 22.0328 | 12.07 | 700 | 22.1319 | 0.4096 | 0.4040 | |
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| 22.0328 | 13.79 | 800 | 23.1465 | 0.3884 | 0.3602 | |
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| 22.0328 | 15.52 | 900 | 23.6087 | 0.3907 | 0.3658 | |
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| 15.8082 | 17.24 | 1000 | 24.1019 | 0.3968 | 0.3767 | |
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| 15.8082 | 18.97 | 1100 | 24.2550 | 0.3973 | 0.3850 | |
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| 15.8082 | 20.69 | 1200 | 23.9667 | 0.4092 | 0.4043 | |
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| 15.8082 | 22.41 | 1300 | 25.2656 | 0.4145 | 0.4010 | |
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| 15.8082 | 24.14 | 1400 | 26.0200 | 0.3893 | 0.3638 | |
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| 11.3074 | 25.86 | 1500 | 25.2350 | 0.4101 | 0.3887 | |
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| 11.3074 | 27.59 | 1600 | 25.8133 | 0.4012 | 0.3853 | |
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| 11.3074 | 29.31 | 1700 | 25.8673 | 0.3959 | 0.3838 | |
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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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