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--- |
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library_name: transformers |
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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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- accuracy |
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model-index: |
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- name: crowd_sourced_web_classifier |
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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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# crowd_sourced_web_classifier |
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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: 1.2894 |
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- Accuracy: 0.5852 |
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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: 0.002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.143 | 1.0 | 79 | 1.9131 | 0.3741 | |
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| 1.6912 | 2.0 | 158 | 1.5070 | 0.4519 | |
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| 1.5696 | 3.0 | 237 | 1.3278 | 0.5926 | |
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| 1.4828 | 4.0 | 316 | 1.2894 | 0.5852 | |
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### Framework versions |
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- Transformers 4.57.2 |
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- Pytorch 2.9.0 |
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- Datasets 4.4.1 |
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- Tokenizers 0.22.1 |
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