deberta-v3-large-survey-cross_passage_consistency-rater-all-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: 0.4020
- Krippendorff: 0.8066
- Spearman: 0.8930
- Absolute Agreement: 0.8848
- Agreement Within One: 0.9447
Model description
More information needed
Intended uses & limitations
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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 | 55 | 1.8997 | -0.2987 | 0.2073 | 0.0556 | 0.9028 |
No log | 2.0 | 110 | 1.8795 | -0.3017 | -0.0377 | 0.0833 | 0.9028 |
No log | 3.0 | 165 | 1.8738 | -0.0086 | 0.0516 | 0.2778 | 0.7778 |
No log | 4.0 | 220 | 1.8663 | -0.0943 | -0.0377 | 0.3472 | 0.7361 |
No log | 5.0 | 275 | 1.8618 | -0.0943 | -0.0377 | 0.3472 | 0.7361 |
No log | 6.0 | 330 | 2.0154 | -0.2704 | nan | 0.3194 | 0.6667 |
No log | 7.0 | 385 | 1.9047 | -0.2704 | nan | 0.3194 | 0.6667 |
No log | 8.0 | 440 | 1.7587 | -0.2704 | nan | 0.3194 | 0.6667 |
No log | 9.0 | 495 | 1.6830 | -0.2704 | nan | 0.3194 | 0.6667 |
1.409 | 10.0 | 550 | 1.6436 | -0.2704 | nan | 0.3194 | 0.6667 |
1.409 | 11.0 | 605 | 1.6273 | -0.2704 | nan | 0.3194 | 0.6667 |
1.409 | 12.0 | 660 | 1.5649 | -0.2505 | 0.1100 | 0.3333 | 0.6667 |
1.409 | 13.0 | 715 | 1.5027 | -0.0705 | 0.4448 | 0.4167 | 0.6806 |
1.409 | 14.0 | 770 | 1.5082 | 0.0375 | 0.4258 | 0.4028 | 0.6944 |
1.409 | 15.0 | 825 | 1.3945 | 0.0492 | 0.5924 | 0.4861 | 0.7083 |
1.409 | 16.0 | 880 | 1.3575 | 0.0458 | 0.5905 | 0.4861 | 0.6806 |
1.409 | 17.0 | 935 | 1.3444 | 0.0492 | 0.5924 | 0.4861 | 0.7083 |
1.409 | 18.0 | 990 | 1.2574 | 0.1791 | 0.5461 | 0.5278 | 0.7778 |
0.7706 | 19.0 | 1045 | 1.2676 | 0.0357 | 0.5486 | 0.5139 | 0.7361 |
0.7706 | 20.0 | 1100 | 1.2345 | 0.0376 | 0.5548 | 0.5278 | 0.7222 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
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