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hbertv2-Massive-intent
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9457
- Accuracy: 0.8515
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 |
|---|---|---|---|---|
| 2.1277 | 1.0 | 180 | 1.0263 | 0.7364 |
| 0.9042 | 2.0 | 360 | 0.8013 | 0.7875 |
| 0.6379 | 3.0 | 540 | 0.8182 | 0.7914 |
| 0.4865 | 4.0 | 720 | 0.8074 | 0.7973 |
| 0.3637 | 5.0 | 900 | 0.7780 | 0.8190 |
| 0.3019 | 6.0 | 1080 | 0.7656 | 0.8288 |
| 0.2218 | 7.0 | 1260 | 0.8253 | 0.8254 |
| 0.1741 | 8.0 | 1440 | 0.8295 | 0.8239 |
| 0.1316 | 9.0 | 1620 | 0.8590 | 0.8308 |
| 0.1011 | 10.0 | 1800 | 0.8465 | 0.8431 |
| 0.078 | 11.0 | 1980 | 0.9007 | 0.8401 |
| 0.0573 | 12.0 | 2160 | 0.9133 | 0.8470 |
| 0.0382 | 13.0 | 2340 | 0.9233 | 0.8470 |
| 0.0247 | 14.0 | 2520 | 0.9365 | 0.8490 |
| 0.0148 | 15.0 | 2700 | 0.9457 | 0.8515 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
