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bert-small-juman-bpe
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.6317
- Loss: 1.7829
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: 0.0001
- train_batch_size: 256
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 768
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 14
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Accuracy | Validation Loss |
---|---|---|---|---|
2.3892 | 1.0 | 69472 | 0.5637 | 2.2498 |
2.2219 | 2.0 | 138944 | 0.5873 | 2.0785 |
2.1453 | 3.0 | 208416 | 0.5984 | 2.0019 |
2.1 | 4.0 | 277888 | 0.6059 | 1.9531 |
2.068 | 5.0 | 347360 | 0.6106 | 1.9169 |
2.0405 | 6.0 | 416832 | 0.6146 | 1.8921 |
2.0174 | 7.0 | 486304 | 0.6175 | 1.8711 |
2.0002 | 8.0 | 555776 | 0.6205 | 1.8527 |
1.9838 | 9.0 | 625248 | 0.6225 | 1.8381 |
1.9691 | 10.0 | 694720 | 0.6248 | 1.8239 |
1.9551 | 11.0 | 764192 | 0.6265 | 1.8125 |
1.9406 | 12.0 | 833664 | 0.6288 | 1.8002 |
1.9293 | 13.0 | 903136 | 0.6310 | 1.7871 |
1.9247 | 14.0 | 972608 | 0.6317 | 1.7829 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.12.0+cu116
- Datasets 2.2.2
- Tokenizers 0.12.1