bert-base-finetuned-sts
This model is a fine-tuned version of klue/bert-base on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5657
- Pearsonr: 0.8375
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: 2e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearsonr |
|---|---|---|---|---|
| No log | 1.0 | 92 | 0.8280 | 0.7680 |
| No log | 2.0 | 184 | 0.6602 | 0.8185 |
| No log | 3.0 | 276 | 0.5939 | 0.8291 |
| No log | 4.0 | 368 | 0.5765 | 0.8367 |
| No log | 5.0 | 460 | 0.5657 | 0.8375 |
Framework versions
- Transformers 4.9.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
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