bert_12_layer_model_v2_complete_training_new_120
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_96 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4439
- Accuracy: 0.5517
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 |
---|---|---|---|---|
2.7038 | 0.08 | 10000 | 2.6207 | 0.5282 |
2.6766 | 0.16 | 20000 | 2.5968 | 0.5309 |
2.6536 | 0.25 | 30000 | 2.5717 | 0.5346 |
2.645 | 0.33 | 40000 | 2.5576 | 0.5365 |
2.6164 | 0.41 | 50000 | 2.5344 | 0.5396 |
2.6027 | 0.49 | 60000 | 2.5164 | 0.5419 |
2.5779 | 0.57 | 70000 | 2.5001 | 0.5443 |
2.5642 | 0.66 | 80000 | 2.4863 | 0.5460 |
2.5439 | 0.74 | 90000 | 2.4716 | 0.5476 |
2.5344 | 0.82 | 100000 | 2.4551 | 0.5502 |
2.5314 | 0.9 | 110000 | 2.4439 | 0.5517 |
Framework versions
- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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