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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: 0.7548
- Accuracy: 0.8162
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6014 | 1.0 | 154 | 0.5832 | 0.7080 |
0.4314 | 2.0 | 308 | 0.5388 | 0.7956 |
0.38 | 3.0 | 462 | 0.4447 | 0.7518 |
0.0704 | 4.0 | 616 | 0.7324 | 0.8175 |
0.015 | 5.0 | 770 | 0.8301 | 0.8394 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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