add_bert_12_layer_model_complete_training_new_72
This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new_48 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.5543
- Accuracy: 0.1759
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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.8144 | 0.08 | 10000 | 5.7474 | 0.1593 |
| 5.7889 | 0.16 | 20000 | 5.7204 | 0.1604 |
| 5.6347 | 0.25 | 30000 | 5.6966 | 0.1623 |
| 5.7138 | 0.33 | 40000 | 5.6725 | 0.1636 |
| 5.6769 | 0.41 | 50000 | 5.6518 | 0.1658 |
| 5.6603 | 0.49 | 60000 | 5.6290 | 0.1686 |
| 5.5852 | 0.57 | 70000 | 5.6076 | 0.1707 |
| 5.6607 | 0.66 | 80000 | 5.5906 | 0.1720 |
| 5.5823 | 0.74 | 90000 | 5.5719 | 0.1739 |
| 5.6124 | 0.82 | 100000 | 5.5543 | 0.1759 |
Framework versions
- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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