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tiny-vanilla-target-glue-rte
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8038
- Accuracy: 0.6209
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6551 | 6.41 | 500 | 0.6433 | 0.6209 |
| 0.4807 | 12.82 | 1000 | 0.7432 | 0.6245 |
| 0.3119 | 19.23 | 1500 | 0.8938 | 0.6173 |
| 0.1942 | 25.64 | 2000 | 1.0436 | 0.6426 |
| 0.1191 | 32.05 | 2500 | 1.3376 | 0.6209 |
| 0.0889 | 38.46 | 3000 | 1.5793 | 0.6101 |
| 0.0561 | 44.87 | 3500 | 1.8038 | 0.6209 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
