bert_uncased_L-2_H-128_A-2_massive
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.6807
- Accuracy: 0.6734
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 |
|---|---|---|---|---|
| 3.8812 | 1.0 | 180 | 3.6329 | 0.2086 |
| 3.4819 | 2.0 | 360 | 3.2331 | 0.3074 |
| 3.1331 | 3.0 | 540 | 2.9025 | 0.3847 |
| 2.8406 | 4.0 | 720 | 2.6372 | 0.4624 |
| 2.6013 | 5.0 | 900 | 2.4211 | 0.5194 |
| 2.4097 | 6.0 | 1080 | 2.2485 | 0.5539 |
| 2.2504 | 7.0 | 1260 | 2.1084 | 0.5898 |
| 2.1234 | 8.0 | 1440 | 1.9968 | 0.6085 |
| 2.0195 | 9.0 | 1620 | 1.9036 | 0.6316 |
| 1.9345 | 10.0 | 1800 | 1.8336 | 0.6463 |
| 1.8616 | 11.0 | 1980 | 1.7722 | 0.6596 |
| 1.8091 | 12.0 | 2160 | 1.7281 | 0.6645 |
| 1.7704 | 13.0 | 2340 | 1.6984 | 0.6685 |
| 1.7431 | 14.0 | 2520 | 1.6807 | 0.6734 |
| 1.7293 | 15.0 | 2700 | 1.6749 | 0.6729 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1