metadata
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: bert-reg-biencoder-cosine_embedding
results: []
bert-reg-biencoder-cosine_embedding
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4608
- Mse: 0.2163
- Mae: 0.3729
- Pearson Corr: 0.1820
- Spearman Corr: 0.1619
- Cosine Sim: 0.6941
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.5366 | 1.0 | 21 | 0.5212 | 0.1367 | 0.2918 | 0.1078 | 0.1049 | 0.9047 |
| 0.5294 | 2.0 | 42 | 0.5061 | 0.0996 | 0.2390 | 0.1385 | 0.1515 | 0.9048 |
| 0.4811 | 3.0 | 63 | 0.4862 | 0.0855 | 0.2381 | 0.1325 | 0.0899 | 0.8857 |
| 0.4292 | 4.0 | 84 | 0.4494 | 0.1511 | 0.3202 | 0.2155 | 0.1778 | 0.7872 |
| 0.3672 | 5.0 | 105 | 0.4513 | 0.1470 | 0.3067 | 0.2206 | 0.1849 | 0.7980 |
| 0.3259 | 6.0 | 126 | 0.4644 | 0.2209 | 0.3901 | 0.1864 | 0.1662 | 0.6696 |
| 0.2866 | 7.0 | 147 | 0.4608 | 0.2163 | 0.3729 | 0.1820 | 0.1619 | 0.6941 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0