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pretrain1
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: 1.0888
- Accuracy: 0.7783
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 92 | 0.4934 | 0.7563 |
| No log | 2.0 | 184 | 0.5083 | 0.7783 |
| No log | 3.0 | 276 | 0.8579 | 0.7767 |
| No log | 4.0 | 368 | 0.9096 | 0.7814 |
| No log | 5.0 | 460 | 1.1022 | 0.7657 |
| 0.2079 | 6.0 | 552 | 1.0888 | 0.7783 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1
