deberta-v3-large-survey-main_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: 0.3709
- Krippendorff: 0.7891
- Spearman: 0.8055
- Absolute Agreement: 0.9002
- Agreement Within One: 0.9519
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 | 1.9290 | -0.7901 | nan | 0.0556 | 1.0 |
No log | 2.0 | 104 | 1.9260 | -0.7901 | nan | 0.0556 | 1.0 |
No log | 3.0 | 156 | 2.2136 | -0.3366 | nan | 0.1667 | 0.8056 |
No log | 4.0 | 208 | 3.0444 | -0.3366 | nan | 0.1667 | 0.8056 |
No log | 5.0 | 260 | 3.3406 | -0.3366 | nan | 0.1667 | 0.8056 |
No log | 6.0 | 312 | 3.6074 | -0.3366 | nan | 0.1667 | 0.8056 |
No log | 7.0 | 364 | 3.6395 | -0.3366 | nan | 0.1667 | 0.8056 |
No log | 8.0 | 416 | 3.5991 | 0.2720 | 0.1638 | 0.1389 | 0.8611 |
No log | 9.0 | 468 | 3.7407 | 0.2147 | 0.1298 | 0.1389 | 0.8611 |
0.9989 | 10.0 | 520 | 3.8742 | 0.2347 | 0.2208 | 0.1389 | 0.8889 |
0.9989 | 11.0 | 572 | 3.7369 | 0.3144 | 0.3601 | 0.1667 | 0.8889 |
0.9989 | 12.0 | 624 | 3.9522 | 0.2347 | 0.2208 | 0.1389 | 0.8889 |
0.9989 | 13.0 | 676 | 3.4874 | 0.2598 | 0.3174 | 0.1944 | 0.8889 |
0.9989 | 14.0 | 728 | 4.1072 | 0.2420 | 0.1444 | 0.1389 | 0.8611 |
0.9989 | 15.0 | 780 | 4.6448 | 0.3090 | 0.3144 | 0.1389 | 0.9167 |
0.9989 | 16.0 | 832 | 4.2375 | 0.3130 | 0.2379 | 0.1389 | 0.9167 |
0.9989 | 17.0 | 884 | 4.4929 | 0.1724 | 0.1068 | 0.1111 | 0.9167 |
0.9989 | 18.0 | 936 | 4.2319 | 0.2867 | 0.1237 | 0.1389 | 0.8889 |
0.9989 | 19.0 | 988 | 4.3529 | 0.2572 | 0.0514 | 0.1111 | 0.8889 |
0.3366 | 20.0 | 1040 | 4.5277 | 0.2274 | 0.0428 | 0.1111 | 0.8611 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
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