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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-MSV-D2_data-cl-cardiff_cl_only_alpha-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-MSV-D2_data-cl-cardiff_cl_only_alpha-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: 16.2447 |
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- Accuracy: 0.3866 |
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- F1: 0.3858 |
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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: 2222 |
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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 | 1.09 | 250 | 12.0259 | 0.3449 | 0.3171 | |
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| 14.0331 | 2.17 | 500 | 11.3284 | 0.3819 | 0.3694 | |
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| 14.0331 | 3.26 | 750 | 11.1163 | 0.3951 | 0.3941 | |
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| 11.7619 | 4.35 | 1000 | 11.5284 | 0.3796 | 0.3733 | |
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| 11.7619 | 5.43 | 1250 | 11.3713 | 0.4174 | 0.4154 | |
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| 9.9697 | 6.52 | 1500 | 11.7460 | 0.3850 | 0.3770 | |
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| 9.9697 | 7.61 | 1750 | 12.6216 | 0.3927 | 0.3863 | |
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| 8.7178 | 8.7 | 2000 | 12.5277 | 0.4020 | 0.4005 | |
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| 8.7178 | 9.78 | 2250 | 11.8300 | 0.3912 | 0.3911 | |
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| 7.7259 | 10.87 | 2500 | 12.7404 | 0.4051 | 0.4035 | |
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| 7.7259 | 11.96 | 2750 | 13.6012 | 0.4051 | 0.4037 | |
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| 6.6383 | 13.04 | 3000 | 14.1112 | 0.3912 | 0.3884 | |
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| 6.6383 | 14.13 | 3250 | 14.0430 | 0.3920 | 0.3881 | |
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| 5.7088 | 15.22 | 3500 | 13.9183 | 0.3966 | 0.3951 | |
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| 5.7088 | 16.3 | 3750 | 14.5237 | 0.3904 | 0.3858 | |
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| 5.1104 | 17.39 | 4000 | 15.0371 | 0.4012 | 0.4011 | |
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| 5.1104 | 18.48 | 4250 | 15.4539 | 0.3866 | 0.3814 | |
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| 4.587 | 19.57 | 4500 | 14.4770 | 0.3989 | 0.3982 | |
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| 4.587 | 20.65 | 4750 | 15.9417 | 0.4136 | 0.4103 | |
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| 4.1118 | 21.74 | 5000 | 15.0406 | 0.3966 | 0.3966 | |
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| 4.1118 | 22.83 | 5250 | 16.1274 | 0.4020 | 0.4016 | |
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| 3.7338 | 23.91 | 5500 | 15.8530 | 0.3858 | 0.3835 | |
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| 3.7338 | 25.0 | 5750 | 16.3221 | 0.4090 | 0.4074 | |
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| 3.4628 | 26.09 | 6000 | 16.5572 | 0.4028 | 0.4017 | |
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| 3.4628 | 27.17 | 6250 | 16.4879 | 0.3881 | 0.3868 | |
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| 3.3012 | 28.26 | 6500 | 16.4834 | 0.3997 | 0.3995 | |
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| 3.3012 | 29.35 | 6750 | 16.2447 | 0.3866 | 0.3858 | |
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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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