hbertv1-small-wt-48-Massive-intent-emb-comp
This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_small_emb_comp on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8462
- Accuracy: 0.8505
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 |
|---|---|---|---|---|
| 2.1467 | 1.0 | 180 | 1.0602 | 0.7393 |
| 0.8554 | 2.0 | 360 | 0.7646 | 0.7964 |
| 0.5593 | 3.0 | 540 | 0.6846 | 0.8239 |
| 0.3868 | 4.0 | 720 | 0.6673 | 0.8278 |
| 0.2613 | 5.0 | 900 | 0.6909 | 0.8259 |
| 0.1681 | 6.0 | 1080 | 0.7123 | 0.8278 |
| 0.1096 | 7.0 | 1260 | 0.7193 | 0.8318 |
| 0.0687 | 8.0 | 1440 | 0.7653 | 0.8337 |
| 0.0405 | 9.0 | 1620 | 0.7966 | 0.8308 |
| 0.0255 | 10.0 | 1800 | 0.8047 | 0.8441 |
| 0.0145 | 11.0 | 1980 | 0.8415 | 0.8426 |
| 0.0092 | 12.0 | 2160 | 0.8462 | 0.8505 |
| 0.0053 | 13.0 | 2340 | 0.8635 | 0.8465 |
| 0.0031 | 14.0 | 2520 | 0.8625 | 0.8475 |
| 0.0023 | 15.0 | 2700 | 0.8632 | 0.8480 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3