<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
hBERTv2_sst2
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6964
- Accuracy: 0.5092
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6916 | 1.0 | 264 | 0.6999 | 0.5092 |
| 0.6885 | 2.0 | 528 | 0.6978 | 0.5092 |
| 0.6871 | 3.0 | 792 | 0.6984 | 0.5092 |
| 0.6869 | 4.0 | 1056 | 0.6990 | 0.5092 |
| 0.6868 | 5.0 | 1320 | 0.6974 | 0.5092 |
| 0.6869 | 6.0 | 1584 | 0.6980 | 0.5092 |
| 0.6867 | 7.0 | 1848 | 0.6984 | 0.5092 |
| 0.6868 | 8.0 | 2112 | 0.6975 | 0.5092 |
| 0.6868 | 9.0 | 2376 | 0.6964 | 0.5092 |
| 0.6865 | 10.0 | 2640 | 0.6978 | 0.5092 |
| 0.6868 | 11.0 | 2904 | 0.6980 | 0.5092 |
| 0.6865 | 12.0 | 3168 | 0.7001 | 0.5092 |
| 0.6867 | 13.0 | 3432 | 0.6966 | 0.5092 |
| 0.6867 | 14.0 | 3696 | 0.6980 | 0.5092 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
