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bert_12_layer_model_v4_48_massive
This model is a fine-tuned version of gokuls/bert_12_layer_model_v4_complete_training_48 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9030
- Accuracy: 0.8392
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: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.1903 | 1.0 | 180 | 2.2860 | 0.4048 |
| 1.81 | 2.0 | 360 | 1.3971 | 0.6134 |
| 1.1787 | 3.0 | 540 | 1.0028 | 0.7270 |
| 0.8518 | 4.0 | 720 | 0.8662 | 0.7718 |
| 0.6633 | 5.0 | 900 | 0.8229 | 0.7885 |
| 0.5208 | 6.0 | 1080 | 0.8214 | 0.8037 |
| 0.4179 | 7.0 | 1260 | 0.7887 | 0.8008 |
| 0.3308 | 8.0 | 1440 | 0.7357 | 0.8293 |
| 0.2518 | 9.0 | 1620 | 0.7840 | 0.8195 |
| 0.1997 | 10.0 | 1800 | 0.7644 | 0.8283 |
| 0.1472 | 11.0 | 1980 | 0.8304 | 0.8318 |
| 0.1122 | 12.0 | 2160 | 0.8461 | 0.8347 |
| 0.0816 | 13.0 | 2340 | 0.8959 | 0.8328 |
| 0.0601 | 14.0 | 2520 | 0.8811 | 0.8382 |
| 0.0401 | 15.0 | 2700 | 0.9030 | 0.8392 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
