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hbertv2-Massive-intent_48
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_48 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9050
- Accuracy: 0.8583
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 |
|---|---|---|---|---|
| 1.8881 | 1.0 | 180 | 0.9326 | 0.7570 |
| 0.8055 | 2.0 | 360 | 0.7966 | 0.7895 |
| 0.5753 | 3.0 | 540 | 0.7452 | 0.8072 |
| 0.4326 | 4.0 | 720 | 0.7314 | 0.8244 |
| 0.3411 | 5.0 | 900 | 0.7077 | 0.8313 |
| 0.2555 | 6.0 | 1080 | 0.7098 | 0.8406 |
| 0.1892 | 7.0 | 1260 | 0.7549 | 0.8455 |
| 0.1497 | 8.0 | 1440 | 0.7784 | 0.8377 |
| 0.1099 | 9.0 | 1620 | 0.7850 | 0.8510 |
| 0.0881 | 10.0 | 1800 | 0.8535 | 0.8470 |
| 0.0583 | 11.0 | 1980 | 0.8475 | 0.8544 |
| 0.0421 | 12.0 | 2160 | 0.8719 | 0.8524 |
| 0.0267 | 13.0 | 2340 | 0.8989 | 0.8519 |
| 0.0158 | 14.0 | 2520 | 0.9175 | 0.8564 |
| 0.0091 | 15.0 | 2700 | 0.9050 | 0.8583 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
