bert_uncased_L-2_H-256_A-4_sst2
This model is a fine-tuned version of google/bert_uncased_L-2_H-256_A-4 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4074
- Accuracy: 0.8211
Model description
More information needed
Intended uses & limitations
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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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4405 | 1.0 | 264 | 0.4195 | 0.8096 |
0.2935 | 2.0 | 528 | 0.4074 | 0.8211 |
0.2371 | 3.0 | 792 | 0.4241 | 0.8291 |
0.2044 | 4.0 | 1056 | 0.4573 | 0.8291 |
0.1805 | 5.0 | 1320 | 0.4635 | 0.8268 |
0.163 | 6.0 | 1584 | 0.4915 | 0.8326 |
0.1486 | 7.0 | 1848 | 0.5187 | 0.8326 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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google/bert_uncased_L-2_H-256_A-4