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bert-base-uncased-finetuned-wls-manual-8ep-lower
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3345
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.1106 | 0.93 | 7 | 1.9471 |
1.5981 | 2.0 | 15 | 1.5742 |
1.4773 | 2.93 | 22 | 1.4429 |
1.3774 | 4.0 | 30 | 1.4203 |
1.2795 | 4.93 | 37 | 1.2554 |
1.2611 | 6.0 | 45 | 1.2564 |
1.2301 | 6.93 | 52 | 1.2837 |
1.1744 | 7.47 | 56 | 1.3219 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.11.0+cu113
- Datasets 2.14.4
- Tokenizers 0.13.3