mrpc_lemmatized_new
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4643
- Accuracy: 0.8058
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: 16
- eval_batch_size: 16
- 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 | Accuracy |
---|---|---|---|---|
0.5449 | 1.0 | 255 | 0.4622 | 0.7925 |
0.3556 | 2.0 | 510 | 0.4824 | 0.7890 |
0.2135 | 3.0 | 765 | 0.6725 | 0.7826 |
0.1251 | 4.0 | 1020 | 0.9652 | 0.7994 |
0.0845 | 5.0 | 1275 | 0.9354 | 0.8023 |
0.0431 | 6.0 | 1530 | 1.0782 | 0.7959 |
0.0287 | 7.0 | 1785 | 1.2790 | 0.8052 |
0.0186 | 8.0 | 2040 | 1.1717 | 0.8075 |
0.0186 | 9.0 | 2295 | 1.2979 | 0.8104 |
0.0079 | 10.0 | 2550 | 1.4014 | 0.8070 |
0.0071 | 11.0 | 2805 | 1.4469 | 0.8029 |
0.0072 | 12.0 | 3060 | 1.4551 | 0.8064 |
0.0043 | 13.0 | 3315 | 1.4443 | 0.8081 |
0.0041 | 14.0 | 3570 | 1.4639 | 0.8093 |
0.0015 | 15.0 | 3825 | 1.4643 | 0.8058 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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