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hbertv1-tiny-wt-frz-48-Massive-intent-emb-comp
This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_tiny_emb_comp_frz on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8947
- Accuracy: 0.7787
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 |
|---|---|---|---|---|
| 3.6262 | 1.0 | 180 | 3.0736 | 0.2892 |
| 2.6684 | 2.0 | 360 | 2.2654 | 0.4206 |
| 2.0129 | 3.0 | 540 | 1.7714 | 0.5396 |
| 1.5846 | 4.0 | 720 | 1.4366 | 0.6522 |
| 1.2957 | 5.0 | 900 | 1.2535 | 0.6950 |
| 1.0996 | 6.0 | 1080 | 1.1380 | 0.7098 |
| 0.9632 | 7.0 | 1260 | 1.0479 | 0.7334 |
| 0.861 | 8.0 | 1440 | 1.0077 | 0.7570 |
| 0.7925 | 9.0 | 1620 | 0.9793 | 0.7664 |
| 0.7277 | 10.0 | 1800 | 0.9500 | 0.7664 |
| 0.6832 | 11.0 | 1980 | 0.9333 | 0.7683 |
| 0.6476 | 12.0 | 2160 | 0.9121 | 0.7737 |
| 0.6167 | 13.0 | 2340 | 0.9049 | 0.7767 |
| 0.5925 | 14.0 | 2520 | 0.9038 | 0.7767 |
| 0.5797 | 15.0 | 2700 | 0.8947 | 0.7787 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3
