metadata
base_model: gokuls/HBERTv1_48_L12_H768_A12
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L12_H768_A12_massive_data_augmented
results: []
HBERTv1_48_L12_H768_A12_massive_data_augmented
This model is a fine-tuned version of gokuls/HBERTv1_48_L12_H768_A12 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6902
- Accuracy: 0.8377
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 |
|---|---|---|---|---|
| 1.0914 | 1.0 | 4000 | 0.6902 | 0.8377 |
| 0.6178 | 2.0 | 8000 | 0.6890 | 0.8283 |
| 0.463 | 3.0 | 12000 | 0.7721 | 0.8254 |
| 0.3683 | 4.0 | 16000 | 0.7829 | 0.8288 |
| 0.3005 | 5.0 | 20000 | 0.8556 | 0.8303 |
| 0.2502 | 6.0 | 24000 | 0.9171 | 0.8214 |
| 0.2106 | 7.0 | 28000 | 1.0074 | 0.8160 |
| 0.1779 | 8.0 | 32000 | 1.0923 | 0.8239 |
| 0.1506 | 9.0 | 36000 | 1.1525 | 0.8254 |
| 0.1259 | 10.0 | 40000 | 1.2103 | 0.8249 |
| 0.1059 | 11.0 | 44000 | 1.3093 | 0.8269 |
| 0.0894 | 12.0 | 48000 | 1.4000 | 0.8288 |
| 0.0745 | 13.0 | 52000 | 1.5050 | 0.8313 |
| 0.0624 | 14.0 | 56000 | 1.5424 | 0.8288 |
| 0.0521 | 15.0 | 60000 | 1.5973 | 0.8308 |
Framework versions
- Transformers 4.34.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.6
- Tokenizers 0.14.1