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--- |
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base_model: finiteautomata/beto-sentiment-analysis |
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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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model-index: |
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- name: beto-sentiment-analysis-finetuned-detests-wandb24 |
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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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# beto-sentiment-analysis-finetuned-detests-wandb24 |
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This model is a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6204 |
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- Accuracy: 0.8674 |
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- F1-score: 0.7993 |
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- Precision: 0.8225 |
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- Recall: 0.7822 |
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- Auc: 0.7822 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:| |
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| 0.393 | 1.0 | 77 | 0.3365 | 0.8592 | 0.7633 | 0.8424 | 0.7287 | 0.7287 | |
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| 0.1947 | 2.0 | 154 | 0.3843 | 0.8396 | 0.7845 | 0.7716 | 0.8023 | 0.8023 | |
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| 0.0597 | 3.0 | 231 | 0.5486 | 0.8740 | 0.8046 | 0.8398 | 0.7814 | 0.7814 | |
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| 0.0028 | 4.0 | 308 | 0.6204 | 0.8674 | 0.7993 | 0.8225 | 0.7822 | 0.7822 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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