deberta-v3-large-survey-related_passage_consistency-rater-half-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: 0.0922
- Krippendorff: 0.9507
- Spearman: 0.9810
- Absolute Agreement: 0.9748
- Agreement Within One: 0.9964
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 | 52 | 2.0495 | -0.3986 | nan | 0.0833 | 0.9722 |
| No log | 2.0 | 104 | 2.0425 | -0.3986 | nan | 0.0833 | 0.9722 |
| No log | 3.0 | 156 | 2.0507 | -0.3786 | -0.3801 | 0.1667 | 0.8889 |
| No log | 4.0 | 208 | 2.6716 | -0.3464 | nan | 0.25 | 0.8889 |
| No log | 5.0 | 260 | 3.0110 | -0.3464 | nan | 0.25 | 0.8889 |
| No log | 6.0 | 312 | 2.9109 | -0.3464 | nan | 0.25 | 0.8889 |
| No log | 7.0 | 364 | 3.3403 | -0.3464 | nan | 0.25 | 0.8889 |
| No log | 8.0 | 416 | 2.6483 | -0.3464 | nan | 0.25 | 0.8889 |
| No log | 9.0 | 468 | 3.0075 | -0.3464 | nan | 0.25 | 0.8889 |
| 0.8825 | 10.0 | 520 | 3.2051 | -0.3464 | nan | 0.25 | 0.8889 |
| 0.8825 | 11.0 | 572 | 3.0661 | -0.3675 | -0.2582 | 0.2222 | 0.8889 |
| 0.8825 | 12.0 | 624 | 3.6486 | -0.3570 | -0.3583 | 0.2778 | 0.8889 |
| 0.8825 | 13.0 | 676 | 3.9220 | -0.3748 | -0.4156 | 0.2778 | 0.8889 |
| 0.8825 | 14.0 | 728 | 4.3003 | -0.3021 | -0.2901 | 0.3056 | 0.9167 |
| 0.8825 | 15.0 | 780 | 4.5146 | -0.3021 | -0.2901 | 0.3056 | 0.9167 |
| 0.8825 | 16.0 | 832 | 4.9068 | -0.2444 | -0.3129 | 0.25 | 0.9167 |
| 0.8825 | 17.0 | 884 | 4.8181 | -0.2444 | -0.3129 | 0.25 | 0.9167 |
| 0.8825 | 18.0 | 936 | 5.1541 | -0.2444 | -0.3129 | 0.25 | 0.9167 |
| 0.8825 | 19.0 | 988 | 4.4155 | -0.1643 | -0.2413 | 0.25 | 0.9167 |
| 0.2028 | 20.0 | 1040 | 5.5223 | -0.2687 | -0.3385 | 0.25 | 0.9167 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1