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olm-bert-tiny-december-2022-target-glue-stsb
This model is a fine-tuned version of muhtasham/olm-bert-tiny-december-2022 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4058
- Pearson: 0.3207
- Spearmanr: 0.3227
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
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
|---|---|---|---|---|---|
| 3.7225 | 2.78 | 500 | 2.3571 | 0.0394 | 0.0504 |
| 1.9638 | 5.56 | 1000 | 2.3486 | 0.1721 | 0.1893 |
| 1.7812 | 8.33 | 1500 | 2.3649 | 0.2248 | 0.2401 |
| 1.5724 | 11.11 | 2000 | 2.3334 | 0.2645 | 0.2767 |
| 1.3776 | 13.89 | 2500 | 2.4034 | 0.2785 | 0.2861 |
| 1.2174 | 16.67 | 3000 | 2.3773 | 0.2963 | 0.3043 |
| 1.0875 | 19.44 | 3500 | 2.3327 | 0.3213 | 0.3205 |
| 0.9406 | 22.22 | 4000 | 2.3715 | 0.3216 | 0.3222 |
| 0.8757 | 25.0 | 4500 | 2.3264 | 0.3274 | 0.3281 |
| 0.7946 | 27.78 | 5000 | 2.4058 | 0.3207 | 0.3227 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
