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bert-finetuned-sent-analysis
This model is a fine-tuned version of bert-base-cased on the twitter-sentiment-analysis dataset. It achieves the following results on the evaluation set:
- Loss: 0.6462
- Accuracy: 0.8476
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4013 | 1.0 | 14999 | 0.3686 | 0.8394 |
| 0.3354 | 2.0 | 29998 | 0.4543 | 0.8493 |
| 0.2539 | 3.0 | 44997 | 0.6462 | 0.8476 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2
