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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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- f1 |
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model-index: |
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- name: xlm-roberta-base-finetuned-emotion |
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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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# xlm-roberta-base-finetuned-emotion |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/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: 0.1856 |
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- Accuracy: 0.9395 |
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- F1: 0.9398 |
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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: 64 |
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- eval_batch_size: 64 |
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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: linear |
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- num_epochs: 10 |
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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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| 0.1374 | 1.0 | 250 | 0.1631 | 0.9335 | 0.9342 | |
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| 0.1038 | 2.0 | 500 | 0.1772 | 0.9335 | 0.9332 | |
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| 0.0883 | 3.0 | 750 | 0.1705 | 0.9375 | 0.9384 | |
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| 0.0788 | 4.0 | 1000 | 0.1524 | 0.9395 | 0.9392 | |
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| 0.0764 | 5.0 | 1250 | 0.1506 | 0.9375 | 0.9375 | |
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| 0.0661 | 6.0 | 1500 | 0.1856 | 0.9395 | 0.9398 | |
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| 0.0578 | 7.0 | 1750 | 0.1819 | 0.934 | 0.9338 | |
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| 0.0483 | 8.0 | 2000 | 0.1799 | 0.9345 | 0.9344 | |
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| 0.0417 | 9.0 | 2250 | 0.1854 | 0.9385 | 0.9386 | |
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| 0.0307 | 10.0 | 2500 | 0.1939 | 0.9375 | 0.9377 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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