roberta-base-bne-finetuned-multi-sentiment
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7116
- Accuracy: 0.6914
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.809 | 1.0 | 115 | 0.7168 | 0.6852 |
| 0.6101 | 2.0 | 230 | 0.7116 | 0.6914 |
Framework versions
- Transformers 4.40.2
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for OscarGalavizC/roberta-base-bne-finetuned-multi-sentiment
Base model
BSC-LT/roberta-base-bne