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--- |
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library_name: transformers |
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license: mit |
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base_model: 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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: emotion_roberta_weighted |
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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_roberta_weighted |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2084 |
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- Accuracy: 0.9315 |
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- Precision: 0.9379 |
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- Recall: 0.9315 |
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- F1: 0.9331 |
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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: 16 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.3177 | 1.0 | 1000 | 0.2423 | 0.918 | 0.9245 | 0.918 | 0.9195 | |
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| 0.1804 | 2.0 | 2000 | 0.1776 | 0.931 | 0.9366 | 0.931 | 0.9317 | |
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| 0.1504 | 3.0 | 3000 | 0.1740 | 0.935 | 0.9410 | 0.935 | 0.9362 | |
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| 0.1203 | 4.0 | 4000 | 0.1723 | 0.9405 | 0.9438 | 0.9405 | 0.9413 | |
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| 0.0889 | 5.0 | 5000 | 0.2068 | 0.939 | 0.9420 | 0.939 | 0.9398 | |
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### Framework versions |
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- Transformers 4.57.2 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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