bert_uncased_L-4_H-128_A-2_massive
This model is a fine-tuned version of google/bert_uncased_L-4_H-128_A-2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.5917
- Accuracy: 0.7122
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 |
|---|---|---|---|---|
| 3.8362 | 1.0 | 180 | 3.5577 | 0.2750 |
| 3.3785 | 2.0 | 360 | 3.1194 | 0.4215 |
| 3.0059 | 3.0 | 540 | 2.7843 | 0.4845 |
| 2.7219 | 4.0 | 720 | 2.5372 | 0.5273 |
| 2.4947 | 5.0 | 900 | 2.3286 | 0.5578 |
| 2.3072 | 6.0 | 1080 | 2.1582 | 0.5947 |
| 2.1494 | 7.0 | 1260 | 2.0276 | 0.6232 |
| 2.0206 | 8.0 | 1440 | 1.9108 | 0.6375 |
| 1.9207 | 9.0 | 1620 | 1.8206 | 0.6704 |
| 1.83 | 10.0 | 1800 | 1.7500 | 0.6891 |
| 1.7592 | 11.0 | 1980 | 1.6872 | 0.7004 |
| 1.7011 | 12.0 | 2160 | 1.6489 | 0.7019 |
| 1.6627 | 13.0 | 2340 | 1.6160 | 0.7093 |
| 1.6347 | 14.0 | 2520 | 1.5992 | 0.7118 |
| 1.6216 | 15.0 | 2700 | 1.5917 | 0.7122 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1