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hbertv1-mini-wt-48-Massive-intent-emb-comp
This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_mini_emb_comp on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.7077
- Accuracy: 0.8411
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 |
|---|---|---|---|---|
| 2.8713 | 1.0 | 180 | 1.8255 | 0.5903 |
| 1.4406 | 2.0 | 360 | 1.1089 | 0.7177 |
| 0.9491 | 3.0 | 540 | 0.8839 | 0.7727 |
| 0.7165 | 4.0 | 720 | 0.7622 | 0.8072 |
| 0.5574 | 5.0 | 900 | 0.7180 | 0.8121 |
| 0.4491 | 6.0 | 1080 | 0.7020 | 0.8224 |
| 0.3617 | 7.0 | 1260 | 0.6915 | 0.8244 |
| 0.291 | 8.0 | 1440 | 0.6727 | 0.8352 |
| 0.2355 | 9.0 | 1620 | 0.6822 | 0.8362 |
| 0.1915 | 10.0 | 1800 | 0.6960 | 0.8293 |
| 0.1569 | 11.0 | 1980 | 0.7021 | 0.8367 |
| 0.1296 | 12.0 | 2160 | 0.7077 | 0.8411 |
| 0.1087 | 13.0 | 2340 | 0.7080 | 0.8406 |
| 0.0931 | 14.0 | 2520 | 0.7152 | 0.8411 |
| 0.0839 | 15.0 | 2700 | 0.7203 | 0.8401 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3
