hbertv1-Massive-intent-48-emb-comp-gelu
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48_gelu on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9566
- Accuracy: 0.8028
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 |
|---|---|---|---|---|
| 3.4622 | 1.0 | 180 | 3.0181 | 0.2169 |
| 2.7526 | 2.0 | 360 | 2.4760 | 0.3168 |
| 2.188 | 3.0 | 540 | 1.9627 | 0.4368 |
| 1.7069 | 4.0 | 720 | 1.5603 | 0.5568 |
| 1.3045 | 5.0 | 900 | 1.3354 | 0.6345 |
| 1.0621 | 6.0 | 1080 | 1.1726 | 0.6862 |
| 0.8745 | 7.0 | 1260 | 1.0703 | 0.7226 |
| 0.7286 | 8.0 | 1440 | 0.9905 | 0.7516 |
| 0.6005 | 9.0 | 1620 | 0.9881 | 0.7644 |
| 0.5021 | 10.0 | 1800 | 0.9661 | 0.7732 |
| 0.4208 | 11.0 | 1980 | 0.9621 | 0.7787 |
| 0.3524 | 12.0 | 2160 | 0.9480 | 0.7939 |
| 0.282 | 13.0 | 2340 | 0.9614 | 0.7924 |
| 0.2327 | 14.0 | 2520 | 0.9525 | 0.7969 |
| 0.1912 | 15.0 | 2700 | 0.9566 | 0.8028 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for gokuls/hbertv1-Massive-intent-48-emb-comp-gelu
Finetuned
this model