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HBERTv1_48_L6_H512_A8_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L6_H512_A8 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8008
- Accuracy: 0.8554
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 |
|---|---|---|---|---|
| 2.2378 | 1.0 | 180 | 1.0048 | 0.7477 |
| 0.8333 | 2.0 | 360 | 0.7230 | 0.8091 |
| 0.5543 | 3.0 | 540 | 0.6624 | 0.8308 |
| 0.3904 | 4.0 | 720 | 0.6289 | 0.8485 |
| 0.2796 | 5.0 | 900 | 0.6249 | 0.8446 |
| 0.2095 | 6.0 | 1080 | 0.6813 | 0.8455 |
| 0.1532 | 7.0 | 1260 | 0.6995 | 0.8421 |
| 0.1142 | 8.0 | 1440 | 0.6917 | 0.8475 |
| 0.0826 | 9.0 | 1620 | 0.7257 | 0.8539 |
| 0.0617 | 10.0 | 1800 | 0.7759 | 0.8470 |
| 0.0415 | 11.0 | 1980 | 0.7927 | 0.8529 |
| 0.028 | 12.0 | 2160 | 0.7841 | 0.8539 |
| 0.0203 | 13.0 | 2340 | 0.8027 | 0.8510 |
| 0.0131 | 14.0 | 2520 | 0.8008 | 0.8554 |
| 0.0102 | 15.0 | 2700 | 0.8058 | 0.8515 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
