bert_12_layer_model_v2_complete_training_new_96
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_72 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6222
- Accuracy: 0.5276
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 |
|---|---|---|---|---|
| 3.0388 | 0.08 | 10000 | 2.9330 | 0.4848 |
| 2.9843 | 0.16 | 20000 | 2.8849 | 0.4916 |
| 2.9373 | 0.25 | 30000 | 2.8368 | 0.4984 |
| 2.9099 | 0.33 | 40000 | 2.8001 | 0.5033 |
| 2.8637 | 0.41 | 50000 | 2.7610 | 0.5085 |
| 2.8368 | 0.49 | 60000 | 2.7313 | 0.5126 |
| 2.7988 | 0.57 | 70000 | 2.7014 | 0.5167 |
| 2.7719 | 0.66 | 80000 | 2.6760 | 0.5199 |
| 2.7385 | 0.74 | 90000 | 2.6492 | 0.5234 |
| 2.7161 | 0.82 | 100000 | 2.6222 | 0.5276 |
Framework versions
- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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