distilBert_cased_for_binary_sentiment_classification
This model is a fine-tuned version of distilbert/distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2352
- Accuracy: 0.923
- F1: 0.9199
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2856 | 1.0 | 1000 | 0.2463 | 0.913 | 0.9096 |
| 0.2074 | 2.0 | 2000 | 0.2352 | 0.923 | 0.9199 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for ThoMyh/distilBert_cased_for_binary_sentiment_classification
Base model
distilbert/distilbert-base-cased