bert_12_layer_model_v2_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: 5.5272
- Accuracy: 0.1983
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 |
---|---|---|---|---|
6.5761 | 0.08 | 10000 | 6.5404 | 0.1269 |
6.3286 | 0.16 | 20000 | 6.3053 | 0.1409 |
6.2283 | 0.25 | 30000 | 6.2131 | 0.1449 |
6.1756 | 0.33 | 40000 | 6.1536 | 0.1478 |
6.1292 | 0.41 | 50000 | 6.1186 | 0.1487 |
6.1008 | 0.49 | 60000 | 6.0845 | 0.1494 |
6.0718 | 0.57 | 70000 | 6.0606 | 0.1504 |
5.9008 | 0.66 | 80000 | 5.8655 | 0.1578 |
5.797 | 0.74 | 90000 | 5.7561 | 0.1695 |
5.6959 | 0.82 | 100000 | 5.6441 | 0.1832 |
5.5955 | 0.9 | 110000 | 5.5272 | 0.1983 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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