CONTEXT_two
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9806
- Precision: 0.6800
- Recall: 0.6711
- F1: 0.6715
- Accuracy: 0.6711
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: 1e-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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.3915 | 0.31 | 15 | 1.3670 | 0.4926 | 0.4211 | 0.3467 | 0.4211 |
| 1.3405 | 0.62 | 30 | 1.3368 | 0.6504 | 0.4737 | 0.4176 | 0.4737 |
| 1.3104 | 0.94 | 45 | 1.2744 | 0.6319 | 0.5526 | 0.5575 | 0.5526 |
| 1.2038 | 1.25 | 60 | 1.1973 | 0.6648 | 0.6053 | 0.6130 | 0.6053 |
| 1.1289 | 1.56 | 75 | 1.1413 | 0.6826 | 0.6842 | 0.6827 | 0.6842 |
| 1.0146 | 1.88 | 90 | 1.0708 | 0.6920 | 0.6316 | 0.6313 | 0.6316 |
| 0.9391 | 2.19 | 105 | 1.0283 | 0.6488 | 0.6184 | 0.6174 | 0.6184 |
| 0.9295 | 2.5 | 120 | 0.9971 | 0.7229 | 0.6974 | 0.7025 | 0.6974 |
| 0.8569 | 2.81 | 135 | 0.9806 | 0.6800 | 0.6711 | 0.6715 | 0.6711 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
distilbert/distilbert-base-cased