BiBert-Classification
This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0853
- Accuracy: 0.7433
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0981 | 1.0 | 9718 | 1.1034 | 0.7328 |
| 1.0394 | 2.0 | 19436 | 1.0853 | 0.7433 |
| 0.9649 | 3.0 | 29154 | 1.1041 | 0.7362 |
| 0.8884 | 4.0 | 38872 | 1.1618 | 0.7315 |
| 0.8005 | 5.0 | 48590 | 1.2340 | 0.7251 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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