hBERTv2_new_pretrain_sst2
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5217
- Accuracy: 0.7867
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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- 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 |
|---|---|---|---|---|
| 0.3983 | 1.0 | 527 | 0.5217 | 0.7867 |
| 0.262 | 2.0 | 1054 | 0.6636 | 0.7890 |
| 0.2195 | 3.0 | 1581 | 0.5875 | 0.7982 |
| 0.1961 | 4.0 | 2108 | 0.6038 | 0.7970 |
| 0.1804 | 5.0 | 2635 | 0.5681 | 0.7856 |
| 0.1829 | 6.0 | 3162 | 0.6722 | 0.8016 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train gokuls/hBERTv2_new_pretrain_sst2
Evaluation results
- Accuracy on GLUE SST2validation set self-reported0.787