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tiny-vanilla-target-glue-stsb
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8716
- Pearson: 0.8141
- Spearmanr: 0.8126
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
|---|---|---|---|---|---|
| 3.1371 | 2.78 | 500 | 1.1225 | 0.7236 | 0.7292 |
| 0.9656 | 5.56 | 1000 | 1.0702 | 0.7703 | 0.7991 |
| 0.7396 | 8.33 | 1500 | 1.0547 | 0.7931 | 0.8189 |
| 0.6264 | 11.11 | 2000 | 0.9011 | 0.8123 | 0.8214 |
| 0.5242 | 13.89 | 2500 | 0.8999 | 0.8135 | 0.8174 |
| 0.4756 | 16.67 | 3000 | 0.9771 | 0.8142 | 0.8192 |
| 0.4225 | 19.44 | 3500 | 0.9021 | 0.8168 | 0.8176 |
| 0.3879 | 22.22 | 4000 | 0.9447 | 0.8176 | 0.8181 |
| 0.3547 | 25.0 | 4500 | 0.8787 | 0.8226 | 0.8216 |
| 0.3355 | 27.78 | 5000 | 0.9789 | 0.8157 | 0.8169 |
| 0.3143 | 30.56 | 5500 | 0.9259 | 0.8152 | 0.8149 |
| 0.2925 | 33.33 | 6000 | 0.8716 | 0.8141 | 0.8126 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
