bert-reg-crossencoder-contrastive
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: 0.0001
- Mse: 0.2717
- Mae: 0.4451
- Pearson Corr: -0.2034
- Spearman Corr: -0.1953
- Cosine Sim: 0.9027
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | Pearson Corr | Spearman Corr | Cosine Sim |
|---|---|---|---|---|---|---|---|---|
| 0.0148 | 1.0 | 41 | 0.0014 | 0.2889 | 0.4614 | -0.1243 | -0.0625 | 0.9003 |
| 0.0096 | 2.0 | 82 | 0.0074 | 0.3706 | 0.5451 | -0.0433 | -0.0347 | 0.9030 |
| 0.0059 | 3.0 | 123 | 0.0001 | 0.2549 | 0.4285 | -0.0372 | -0.0585 | 0.9032 |
| 0.004 | 4.0 | 164 | 0.0023 | 0.3175 | 0.4940 | -0.0783 | -0.0715 | 0.9029 |
| 0.0026 | 5.0 | 205 | 0.0003 | 0.2770 | 0.4519 | -0.0308 | -0.0070 | 0.9033 |
| 0.0019 | 6.0 | 246 | 0.0002 | 0.2771 | 0.4512 | -0.1884 | -0.1805 | 0.9028 |
| 0.0018 | 7.0 | 287 | 0.0001 | 0.2717 | 0.4451 | -0.2034 | -0.1953 | 0.9027 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1