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--- |
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license: mit |
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base_model: xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: tmp |
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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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# tmp |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/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: 0.3272 |
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- Precision: 0.5560 |
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- Recall: 0.3209 |
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- F1: 0.4069 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
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| 0.7083 | 0.35 | 500 | 0.4423 | 0.2785 | 0.0529 | 0.0889 | |
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| 0.4849 | 0.7 | 1000 | 0.4009 | 0.3623 | 0.1803 | 0.2408 | |
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| 0.4021 | 1.04 | 1500 | 0.3621 | 0.5027 | 0.2212 | 0.3072 | |
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| 0.3276 | 1.39 | 2000 | 0.3606 | 0.4006 | 0.3077 | 0.3481 | |
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| 0.2857 | 1.74 | 2500 | 0.3432 | 0.5073 | 0.25 | 0.3349 | |
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| 0.251 | 2.09 | 3000 | 0.3481 | 0.4431 | 0.3413 | 0.3856 | |
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| 0.2184 | 2.43 | 3500 | 0.3309 | 0.5274 | 0.3353 | 0.4100 | |
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| 0.2162 | 2.78 | 4000 | 0.3411 | 0.4167 | 0.3726 | 0.3934 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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