M6_cross
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0084
- Pearson: 0.9811
- Spearmanr: 0.9075
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: 20
- eval_batch_size: 20
- seed: 25
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 6.0
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
---|---|---|---|---|---|
0.0059 | 1.0 | 105 | 0.0158 | 0.9633 | 0.9054 |
0.001 | 2.0 | 210 | 0.0102 | 0.9770 | 0.9103 |
0.0008 | 3.0 | 315 | 0.0083 | 0.9805 | 0.9052 |
0.0011 | 4.0 | 420 | 0.0075 | 0.9812 | 0.9082 |
0.0017 | 5.0 | 525 | 0.0084 | 0.9811 | 0.9075 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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