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distilbert-base-uncased-finetuned-kagglesentiment
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9463
- Accuracy: 0.65
- F1: 0.5916
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: 64
- eval_batch_size: 64
- 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 | F1 |
|---|---|---|---|---|---|
| 0.9756 | 1.0 | 32 | 1.0037 | 0.599 | 0.4909 |
| 0.8383 | 2.0 | 64 | 0.9463 | 0.65 | 0.5916 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.14.0
