hbertv1-small-wt-48-Massive-intent
This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_small on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.6540
- Accuracy: 0.8672
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 |
|---|---|---|---|---|
| 2.0435 | 1.0 | 180 | 0.8648 | 0.7693 |
| 0.7809 | 2.0 | 360 | 0.6523 | 0.8190 |
| 0.5432 | 3.0 | 540 | 0.5795 | 0.8441 |
| 0.4035 | 4.0 | 720 | 0.5657 | 0.8539 |
| 0.2976 | 5.0 | 900 | 0.5547 | 0.8618 |
| 0.22 | 6.0 | 1080 | 0.5735 | 0.8598 |
| 0.1639 | 7.0 | 1260 | 0.5905 | 0.8554 |
| 0.1281 | 8.0 | 1440 | 0.5916 | 0.8618 |
| 0.0893 | 9.0 | 1620 | 0.6186 | 0.8642 |
| 0.0722 | 10.0 | 1800 | 0.6370 | 0.8642 |
| 0.0513 | 11.0 | 1980 | 0.6540 | 0.8672 |
| 0.039 | 12.0 | 2160 | 0.6762 | 0.8637 |
| 0.0307 | 13.0 | 2340 | 0.6796 | 0.8637 |
| 0.0223 | 14.0 | 2520 | 0.6895 | 0.8657 |
| 0.0169 | 15.0 | 2700 | 0.6918 | 0.8652 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3