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distilbert-base-uncased-finetuned-ft500_6class600
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: 1.6317
- Accuracy: 0.35
- F1: 0.3327
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
1.5717 | 1.0 | 188 | 1.5375 | 0.3067 | 0.2820 |
1.4338 | 2.0 | 376 | 1.5354 | 0.3207 | 0.2824 |
1.3516 | 3.0 | 564 | 1.4852 | 0.3573 | 0.3287 |
1.2722 | 4.0 | 752 | 1.4997 | 0.366 | 0.3534 |
1.1923 | 5.0 | 940 | 1.5474 | 0.362 | 0.3454 |
1.1156 | 6.0 | 1128 | 1.5998 | 0.3547 | 0.3387 |
1.0522 | 7.0 | 1316 | 1.6154 | 0.3473 | 0.3316 |
1.0148 | 8.0 | 1504 | 1.6317 | 0.35 | 0.3327 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1