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bert_12_layer_model_v1_complete_training_new
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.5161
- Accuracy: 0.3159
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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
6.5749 | 0.08 | 10000 | 6.5382 | 0.1269 |
6.3332 | 0.16 | 20000 | 6.3097 | 0.1411 |
6.2343 | 0.25 | 30000 | 6.2182 | 0.1450 |
6.1807 | 0.33 | 40000 | 6.1587 | 0.1478 |
6.0548 | 0.41 | 50000 | 6.0215 | 0.1529 |
5.8862 | 0.49 | 60000 | 5.8339 | 0.1672 |
5.7493 | 0.57 | 70000 | 5.6845 | 0.1878 |
5.596 | 0.66 | 80000 | 5.5063 | 0.2078 |
5.071 | 0.74 | 90000 | 4.8887 | 0.2781 |
4.6869 | 0.82 | 100000 | 4.5161 | 0.3159 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3