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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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model-index: |
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- name: e3_lr2e-05 |
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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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# e3_lr2e-05 |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6436 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 256 |
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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: 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 | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.9961 | 0.1404 | 100 | 1.9416 | |
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| 2.0472 | 0.2808 | 200 | 1.8589 | |
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| 1.9766 | 0.4212 | 300 | 1.8095 | |
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| 1.9319 | 0.5616 | 400 | 1.7736 | |
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| 1.897 | 0.7021 | 500 | 1.7447 | |
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| 1.8743 | 0.8425 | 600 | 1.7370 | |
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| 1.86 | 0.9829 | 700 | 1.7156 | |
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| 1.8431 | 1.1233 | 800 | 1.7071 | |
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| 1.8217 | 1.2637 | 900 | 1.6939 | |
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| 1.8212 | 1.4041 | 1000 | 1.6900 | |
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| 1.8053 | 1.5445 | 1100 | 1.6774 | |
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| 1.7899 | 1.6849 | 1200 | 1.6736 | |
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| 1.799 | 1.8254 | 1300 | 1.6644 | |
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| 1.7845 | 1.9658 | 1400 | 1.6559 | |
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| 1.7704 | 2.1062 | 1500 | 1.6531 | |
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| 1.776 | 2.2466 | 1600 | 1.6528 | |
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| 1.773 | 2.3870 | 1700 | 1.6417 | |
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| 1.7632 | 2.5274 | 1800 | 1.6452 | |
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| 1.7451 | 2.6678 | 1900 | 1.6460 | |
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| 1.7505 | 2.8088 | 2000 | 1.6455 | |
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| 1.7602 | 2.9492 | 2100 | 1.6399 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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