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bert-large-uncased-finetuned-rte
This model is a fine-tuned version of bert-large-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.7653
- Accuracy: 0.7545
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: 2e-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
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 312 | 0.6211 | 0.6643 |
0.6082 | 2.0 | 624 | 0.6857 | 0.6643 |
0.6082 | 3.0 | 936 | 0.7653 | 0.7545 |
0.3509 | 4.0 | 1248 | 1.2287 | 0.7401 |
0.153 | 5.0 | 1560 | 1.5192 | 0.7437 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3