distilbert_km_20_v1_stsb
This model is a fine-tuned version of Hartunka/distilbert_km_20_v1 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 2.2609
- Pearson: 0.2611
- Spearmanr: 0.2472
- Combined Score: 0.2541
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 3.0017 | 1.0 | 23 | 2.2981 | 0.2026 | 0.1931 | 0.1979 |
| 1.9351 | 2.0 | 46 | 2.2676 | 0.2316 | 0.2087 | 0.2201 |
| 1.726 | 3.0 | 69 | 2.2609 | 0.2611 | 0.2472 | 0.2541 |
| 1.4643 | 4.0 | 92 | 2.5773 | 0.2676 | 0.2552 | 0.2614 |
| 1.1579 | 5.0 | 115 | 2.4631 | 0.2834 | 0.2801 | 0.2817 |
| 0.8956 | 6.0 | 138 | 2.5973 | 0.2666 | 0.2589 | 0.2627 |
| 0.6537 | 7.0 | 161 | 2.8749 | 0.2534 | 0.2460 | 0.2497 |
| 0.5065 | 8.0 | 184 | 2.6949 | 0.2854 | 0.2859 | 0.2857 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
- Downloads last month
- -
Model tree for Hartunka/distilbert_km_20_v1_stsb
Base model
Hartunka/distilbert_km_20_v1Dataset used to train Hartunka/distilbert_km_20_v1_stsb
Evaluation results
- Spearmanr on GLUE STSBself-reported0.247