crossencoder-stsb-roberta-base
This model is a fine-tuned version of cross-encoder/stsb-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0011
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: 5e-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: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0152 | 1.0 | 125 | 0.0099 |
| 0.0047 | 2.0 | 250 | 0.0013 |
| 0.0057 | 3.0 | 375 | 0.0025 |
| 0.0032 | 4.0 | 500 | 0.0027 |
| 0.0033 | 5.0 | 625 | 0.0164 |
| 0.0026 | 6.0 | 750 | 0.0002 |
| 0.0034 | 7.0 | 875 | 0.0035 |
| 0.002 | 8.0 | 1000 | 0.0057 |
| 0.002 | 9.0 | 1125 | 0.0016 |
| 0.0016 | 10.0 | 1250 | 0.0017 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.15.1