distilbert-base-uncased-finetuned-sst2
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: 0.3009
- Accuracy: 0.9048
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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 132 | 0.2494 | 0.8968 |
| No log | 2.0 | 264 | 0.2767 | 0.8968 |
| No log | 3.0 | 396 | 0.2810 | 0.9002 |
| 0.195 | 4.0 | 528 | 0.2920 | 0.9025 |
| 0.195 | 5.0 | 660 | 0.3009 | 0.9048 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for winegarj/distilbert-base-uncased-finetuned-sst2
Base model
distilbert/distilbert-base-uncased