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--- |
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library_name: peft |
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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: emotion-model11_0 |
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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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# emotion-model11_0 |
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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: 0.9531 |
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- Accuracy: 0.6135 |
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- F1: 0.5573 |
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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: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 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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| No log | 1.0 | 41 | 1.3368 | 0.3804 | 0.2096 | |
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| 1.3413 | 2.0 | 82 | 1.2883 | 0.3804 | 0.2096 | |
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| 1.2917 | 3.0 | 123 | 1.0577 | 0.5521 | 0.4841 | |
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| 1.1702 | 4.0 | 164 | 1.0247 | 0.5337 | 0.4033 | |
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| 1.1099 | 5.0 | 205 | 0.9804 | 0.5460 | 0.4324 | |
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| 1.1099 | 6.0 | 246 | 0.9531 | 0.6135 | 0.5573 | |
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| 1.0856 | 7.0 | 287 | 0.9336 | 0.6135 | 0.5301 | |
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| 1.0752 | 8.0 | 328 | 0.9257 | 0.5767 | 0.4883 | |
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| 1.0393 | 9.0 | 369 | 0.9182 | 0.5828 | 0.5188 | |
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| 1.0449 | 10.0 | 410 | 0.9131 | 0.5828 | 0.5188 | |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.52.4 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
