deberta-v3-large-survey-main_passage_consistency-rater-gpt4
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3012
- Krippendorff: 0.8426
- Spearman: 0.8656
- Absolute Agreement: 0.9183
- Agreement Within One: 0.9673
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: 6e-06
- 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: 1000
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Krippendorff | Spearman | Absolute Agreement | Agreement Within One |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 50 | 2.0918 | -0.8602 | nan | 0.0139 | 1.0 |
| No log | 2.0 | 100 | 2.0792 | -0.8602 | nan | 0.0139 | 1.0 |
| No log | 3.0 | 150 | 1.8791 | -0.0618 | -0.1346 | 0.25 | 0.8472 |
| No log | 4.0 | 200 | 2.0894 | -0.2303 | nan | 0.375 | 0.8194 |
| No log | 5.0 | 250 | 2.4916 | -0.2303 | nan | 0.375 | 0.8194 |
| No log | 6.0 | 300 | 2.6486 | -0.2303 | nan | 0.375 | 0.8194 |
| No log | 7.0 | 350 | 2.9221 | -0.2303 | nan | 0.375 | 0.8194 |
| No log | 8.0 | 400 | 2.9376 | -0.2303 | nan | 0.375 | 0.8194 |
| No log | 9.0 | 450 | 3.0675 | -0.2303 | nan | 0.375 | 0.8194 |
| 1.0223 | 10.0 | 500 | 3.0166 | -0.2303 | nan | 0.375 | 0.8194 |
| 1.0223 | 11.0 | 550 | 3.3407 | -0.2303 | nan | 0.375 | 0.8194 |
| 1.0223 | 12.0 | 600 | 3.4897 | 0.1396 | 0.2611 | 0.375 | 0.8472 |
| 1.0223 | 13.0 | 650 | 3.8130 | 0.1396 | 0.2611 | 0.375 | 0.8472 |
| 1.0223 | 14.0 | 700 | 4.0549 | 0.1396 | 0.2611 | 0.375 | 0.8472 |
| 1.0223 | 15.0 | 750 | 4.3384 | -0.2303 | nan | 0.375 | 0.8194 |
| 1.0223 | 16.0 | 800 | 4.5561 | -0.2303 | nan | 0.375 | 0.8194 |
| 1.0223 | 17.0 | 850 | 4.4345 | -0.2303 | nan | 0.375 | 0.8194 |
| 1.0223 | 18.0 | 900 | 4.8191 | -0.1764 | -0.0680 | 0.3611 | 0.8194 |
| 1.0223 | 19.0 | 950 | 4.8287 | -0.2303 | nan | 0.375 | 0.8194 |
| 0.2678 | 20.0 | 1000 | 4.6614 | -0.1528 | -0.0976 | 0.3472 | 0.8194 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1