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bert-base-cased-finetuned-wls-manual-10ep
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1918
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.159 | 0.93 | 7 | 1.8408 |
1.6358 | 2.0 | 15 | 1.6173 |
1.5483 | 2.93 | 22 | 1.5092 |
1.3734 | 4.0 | 30 | 1.4044 |
1.3188 | 4.93 | 37 | 1.3874 |
1.2528 | 6.0 | 45 | 1.2883 |
1.1951 | 6.93 | 52 | 1.2463 |
1.1413 | 8.0 | 60 | 1.2215 |
1.1573 | 8.93 | 67 | 1.1365 |
1.1051 | 9.33 | 70 | 1.2449 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.11.0+cu113
- Datasets 2.14.4
- Tokenizers 0.13.3