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bert-base-uncased-finetuned-removed-0530
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: 1.1269
- Accuracy: 0.8745
- F1: 0.8745
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 3180 | 0.5939 | 0.8113 | 0.8113 |
| No log | 2.0 | 6360 | 0.6459 | 0.8189 | 0.8183 |
| No log | 3.0 | 9540 | 0.6523 | 0.8597 | 0.8604 |
| No log | 4.0 | 12720 | 0.8159 | 0.8522 | 0.8521 |
| No log | 5.0 | 15900 | 0.9294 | 0.8601 | 0.8599 |
| No log | 6.0 | 19080 | 1.0066 | 0.8594 | 0.8592 |
| No log | 7.0 | 22260 | 1.0268 | 0.8686 | 0.8689 |
| 0.2451 | 8.0 | 25440 | 1.0274 | 0.8758 | 0.8760 |
| 0.2451 | 9.0 | 28620 | 1.0850 | 0.8726 | 0.8727 |
| 0.2451 | 10.0 | 31800 | 1.1269 | 0.8745 | 0.8745 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1
