bert_uncased_L-2_H-768_A-12-mlm-multi-emails-hq
This model is a fine-tuned version of google/bert_uncased_L-2_H-768_A-12 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9133
- Accuracy: 0.6452
Model description
Small BERT, uncased. 155 MB.
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.3053 | 0.99 | 141 | 2.1758 | 0.6064 |
| 2.1556 | 1.99 | 282 | 2.0587 | 0.6237 |
| 2.0616 | 2.99 | 423 | 1.9780 | 0.6355 |
| 2.0084 | 3.99 | 564 | 1.9317 | 0.6422 |
| 1.9621 | 4.99 | 705 | 1.9133 | 0.6452 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 2.0.0.dev20230129+cu118
- Datasets 2.8.0
- Tokenizers 0.13.1