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HBERTv1_48_L2_H768_A12_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L2_H768_A12 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.7845
- Accuracy: 0.8642
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 |
---|---|---|---|---|
1.4964 | 1.0 | 180 | 0.6712 | 0.8087 |
0.5902 | 2.0 | 360 | 0.5767 | 0.8416 |
0.3724 | 3.0 | 540 | 0.5509 | 0.8510 |
0.2499 | 4.0 | 720 | 0.5592 | 0.8554 |
0.1719 | 5.0 | 900 | 0.5892 | 0.8529 |
0.118 | 6.0 | 1080 | 0.6567 | 0.8505 |
0.0849 | 7.0 | 1260 | 0.6597 | 0.8455 |
0.0656 | 8.0 | 1440 | 0.7050 | 0.8554 |
0.0456 | 9.0 | 1620 | 0.7098 | 0.8593 |
0.0314 | 10.0 | 1800 | 0.7583 | 0.8633 |
0.0213 | 11.0 | 1980 | 0.7845 | 0.8642 |
0.0174 | 12.0 | 2160 | 0.7764 | 0.8613 |
0.0112 | 13.0 | 2340 | 0.7723 | 0.8593 |
0.0076 | 14.0 | 2520 | 0.7828 | 0.8598 |
0.0062 | 15.0 | 2700 | 0.7825 | 0.8603 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0