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hbertv1-wt-frz-48-Massive-intent
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48_frz on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8314
- Accuracy: 0.8746
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 |
|---|---|---|---|---|
| 1.9303 | 1.0 | 180 | 0.8615 | 0.7659 |
| 0.7462 | 2.0 | 360 | 0.6661 | 0.8259 |
| 0.5125 | 3.0 | 540 | 0.6419 | 0.8342 |
| 0.3659 | 4.0 | 720 | 0.6058 | 0.8515 |
| 0.2742 | 5.0 | 900 | 0.6297 | 0.8539 |
| 0.1975 | 6.0 | 1080 | 0.6507 | 0.8510 |
| 0.1486 | 7.0 | 1260 | 0.6978 | 0.8500 |
| 0.1109 | 8.0 | 1440 | 0.7019 | 0.8608 |
| 0.0789 | 9.0 | 1620 | 0.7188 | 0.8598 |
| 0.0579 | 10.0 | 1800 | 0.7707 | 0.8628 |
| 0.0362 | 11.0 | 1980 | 0.7928 | 0.8647 |
| 0.0215 | 12.0 | 2160 | 0.7807 | 0.8697 |
| 0.0115 | 13.0 | 2340 | 0.8247 | 0.8701 |
| 0.0068 | 14.0 | 2520 | 0.8314 | 0.8746 |
| 0.0048 | 15.0 | 2700 | 0.8271 | 0.8731 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3
