IMDB_sentimental_analysis-distilbert-base-uncased
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8789
- Accuracy: 0.8628
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3119 | 1.0 | 4 | 0.4168 | 0.8218 |
| 0.0909 | 2.0 | 8 | 0.3831 | 0.8598 |
| 0.0225 | 3.0 | 12 | 0.4887 | 0.878 |
| 0.0036 | 4.0 | 16 | 0.7360 | 0.8538 |
| 0.0021 | 5.0 | 20 | 0.8774 | 0.8454 |
| 0.0011 | 6.0 | 24 | 0.8836 | 0.8516 |
| 0.0008 | 7.0 | 28 | 0.8761 | 0.8577 |
| 0.0006 | 8.0 | 32 | 0.8758 | 0.8609 |
| 0.0006 | 9.0 | 36 | 0.8777 | 0.8625 |
| 0.0005 | 10.0 | 40 | 0.8789 | 0.8628 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
distilbert/distilbert-base-uncased