bert_test_8
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: 0.7390
- F1: 0.8624
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
1.5054 | 1.0 | 341 | 0.8553 | 0.7042 |
0.7004 | 2.0 | 682 | 0.5741 | 0.8367 |
0.4056 | 3.0 | 1023 | 0.4853 | 0.8504 |
0.2813 | 4.0 | 1364 | 0.4766 | 0.8574 |
0.1813 | 5.0 | 1705 | 0.4964 | 0.8536 |
0.1327 | 6.0 | 2046 | 0.5343 | 0.8648 |
0.1148 | 7.0 | 2387 | 0.6017 | 0.8723 |
0.0755 | 8.0 | 2728 | 0.6251 | 0.8684 |
0.0552 | 9.0 | 3069 | 0.6666 | 0.8624 |
0.0442 | 10.0 | 3410 | 0.6992 | 0.8670 |
0.0308 | 11.0 | 3751 | 0.7045 | 0.8705 |
0.0235 | 12.0 | 4092 | 0.7237 | 0.8607 |
0.0219 | 13.0 | 4433 | 0.7377 | 0.8596 |
0.0249 | 14.0 | 4774 | 0.7384 | 0.8646 |
0.0214 | 15.0 | 5115 | 0.7390 | 0.8624 |
Framework versions
- Transformers 4.27.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
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