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olm-bert-tiny-december-2022-target-glue-mrpc
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: 0.9243
- Accuracy: 0.6299
- F1: 0.7146
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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6093 | 4.35 | 500 | 0.5848 | 0.7034 | 0.7980 |
| 0.5487 | 8.7 | 1000 | 0.5863 | 0.7206 | 0.8087 |
| 0.4724 | 13.04 | 1500 | 0.6881 | 0.6544 | 0.7294 |
| 0.3752 | 17.39 | 2000 | 0.7549 | 0.6520 | 0.7331 |
| 0.276 | 21.74 | 2500 | 0.9243 | 0.6299 | 0.7146 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
