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bert-small-finetuned-glue-rte
This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 2.8715
- Accuracy: 0.6318
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
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 2.62 | 50 | 1.8285 | 0.6318 |
| No log | 5.26 | 100 | 2.0806 | 0.6462 |
| No log | 7.87 | 150 | 2.1598 | 0.6282 |
| No log | 10.51 | 200 | 2.2774 | 0.6318 |
| No log | 13.15 | 250 | 2.3676 | 0.6245 |
| No log | 15.77 | 300 | 2.4581 | 0.6462 |
| No log | 18.41 | 350 | 2.6175 | 0.6354 |
| No log | 21.05 | 400 | 2.6697 | 0.6354 |
| No log | 23.67 | 450 | 2.7717 | 0.6354 |
| 0.0101 | 26.31 | 500 | 2.7975 | 0.6462 |
| 0.0101 | 28.92 | 550 | 2.8532 | 0.6390 |
| 0.0101 | 31.56 | 600 | 2.9054 | 0.6209 |
| 0.0101 | 34.21 | 650 | 2.8715 | 0.6318 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
