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hbertv1-Massive-intent_48_KD
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_48_KD on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8470
- Accuracy: 0.8357
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 |
|---|---|---|---|---|
| 2.994 | 1.0 | 180 | 2.1475 | 0.3901 |
| 1.7222 | 2.0 | 360 | 1.4146 | 0.6011 |
| 1.1889 | 3.0 | 540 | 1.1690 | 0.6990 |
| 0.9256 | 4.0 | 720 | 0.9700 | 0.7545 |
| 0.763 | 5.0 | 900 | 0.8986 | 0.7806 |
| 0.6351 | 6.0 | 1080 | 0.8898 | 0.7787 |
| 0.5374 | 7.0 | 1260 | 0.8604 | 0.7978 |
| 0.4587 | 8.0 | 1440 | 0.8444 | 0.8101 |
| 0.3822 | 9.0 | 1620 | 0.8520 | 0.8087 |
| 0.3301 | 10.0 | 1800 | 0.8309 | 0.8185 |
| 0.2713 | 11.0 | 1980 | 0.8313 | 0.8249 |
| 0.2257 | 12.0 | 2160 | 0.8499 | 0.8254 |
| 0.1947 | 13.0 | 2340 | 0.8375 | 0.8298 |
| 0.162 | 14.0 | 2520 | 0.8428 | 0.8352 |
| 0.1369 | 15.0 | 2700 | 0.8470 | 0.8357 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
