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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: outputs |
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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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# outputs |
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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: 0.1489 |
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- F1 Micro: 0.8209 |
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- Precision Micro: 0.8209 |
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- Recall Micro: 0.8209 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Precision Micro | Recall Micro | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------------:|:------------:| |
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| 0.4507 | 0.7782 | 200 | 0.3227 | 0.0 | 0.0 | 0.0 | |
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| 0.263 | 1.5564 | 400 | 0.2081 | 0.5201 | 0.8744 | 0.3701 | |
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| 0.1789 | 2.3346 | 600 | 0.1686 | 0.7489 | 0.8231 | 0.6870 | |
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| 0.13 | 3.1128 | 800 | 0.1555 | 0.7691 | 0.8074 | 0.7343 | |
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| 0.1063 | 3.8911 | 1000 | 0.1416 | 0.7974 | 0.7649 | 0.8327 | |
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| 0.0844 | 4.6693 | 1200 | 0.1492 | 0.8 | 0.8008 | 0.7992 | |
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| 0.0617 | 5.4475 | 1400 | 0.1449 | 0.8268 | 0.8268 | 0.8268 | |
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| 0.0534 | 6.2257 | 1600 | 0.1388 | 0.8283 | 0.8258 | 0.8307 | |
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| 0.0352 | 7.0039 | 1800 | 0.1471 | 0.8272 | 0.8297 | 0.8248 | |
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| 0.0296 | 7.7821 | 2000 | 0.1489 | 0.8209 | 0.8209 | 0.8209 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.0.post100 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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