deberta-v3-large-survey-cross_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: 0.5957
- Krippendorff: 0.5530
- Spearman: 0.6991
- Absolute Agreement: 0.8221
- Agreement Within One: 0.9002
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 | 1.9600 | -0.4776 | 0.3301 | 0.0556 | 0.9722 |
| No log | 2.0 | 104 | 1.9258 | -0.2795 | 0.2827 | 0.0833 | 0.9722 |
| No log | 3.0 | 156 | 1.9351 | -0.3095 | 0.2873 | 0.0833 | 0.9722 |
| No log | 4.0 | 208 | 2.0079 | -0.1471 | -0.1057 | 0.0833 | 0.8333 |
| No log | 5.0 | 260 | 2.2469 | -0.2860 | nan | 0.1944 | 0.8056 |
| No log | 6.0 | 312 | 2.2186 | -0.2860 | nan | 0.1944 | 0.8056 |
| No log | 7.0 | 364 | 2.2266 | -0.2860 | nan | 0.1944 | 0.8056 |
| No log | 8.0 | 416 | 2.2258 | -0.2860 | nan | 0.1944 | 0.8056 |
| No log | 9.0 | 468 | 2.2048 | -0.2860 | nan | 0.1944 | 0.8056 |
| 1.3796 | 10.0 | 520 | 2.2347 | -0.2860 | nan | 0.1944 | 0.8056 |
| 1.3796 | 11.0 | 572 | 2.2480 | -0.2860 | nan | 0.1944 | 0.8056 |
| 1.3796 | 12.0 | 624 | 2.1409 | -0.2349 | 0.0 | 0.1944 | 0.8056 |
| 1.3796 | 13.0 | 676 | 2.0869 | 0.0452 | 0.1218 | 0.1944 | 0.8333 |
| 1.3796 | 14.0 | 728 | 2.1785 | 0.1597 | 0.2372 | 0.1944 | 0.8611 |
| 1.3796 | 15.0 | 780 | 2.1684 | 0.0452 | 0.1218 | 0.1944 | 0.8333 |
| 1.3796 | 16.0 | 832 | 2.3356 | 0.0185 | 0.1110 | 0.1944 | 0.8333 |
| 1.3796 | 17.0 | 884 | 2.5980 | -0.0694 | 0.0783 | 0.2222 | 0.8333 |
| 1.3796 | 18.0 | 936 | 2.3700 | 0.0944 | 0.2085 | 0.1944 | 0.8611 |
| 1.3796 | 19.0 | 988 | 2.3355 | -0.0396 | 0.0913 | 0.1667 | 0.8611 |
| 0.7039 | 20.0 | 1040 | 2.7088 | -0.0625 | 0.0901 | 0.1667 | 0.8611 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1