deberta-v3-large-survey-fluency-rater-all
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: 0.7178
- Krippendorff: 0.9045
- Spearman: 0.8801
- Absolute Agreement: 0.7396
- Agreement Within One: 0.9608
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 | 55 | 2.0214 | -0.6902 | 0.2469 | 0.0139 | 1.0 |
No log | 2.0 | 110 | 2.0118 | -0.6398 | 0.1978 | 0.0278 | 1.0 |
No log | 3.0 | 165 | 2.0147 | -0.6585 | -0.0351 | 0.0278 | 0.9583 |
No log | 4.0 | 220 | 2.0186 | -0.6499 | -0.1548 | 0.0139 | 0.9306 |
No log | 5.0 | 275 | 1.7283 | -0.2880 | nan | 0.2917 | 0.7222 |
No log | 6.0 | 330 | 1.7079 | -0.2454 | 0.1527 | 0.3056 | 0.7222 |
No log | 7.0 | 385 | 1.6519 | -0.0919 | -0.0671 | 0.3889 | 0.7639 |
No log | 8.0 | 440 | 1.6403 | 0.1140 | -0.0254 | 0.4028 | 0.7778 |
No log | 9.0 | 495 | 1.6711 | -0.1939 | -0.0213 | 0.3333 | 0.75 |
1.5874 | 10.0 | 550 | 1.6714 | -0.0236 | 0.1527 | 0.3056 | 0.7361 |
1.5874 | 11.0 | 605 | 1.5761 | -0.0843 | -0.1552 | 0.4028 | 0.7639 |
1.5874 | 12.0 | 660 | 1.4782 | 0.2760 | 0.1495 | 0.4444 | 0.7917 |
1.5874 | 13.0 | 715 | 1.4679 | 0.1322 | -0.0231 | 0.4028 | 0.7778 |
1.5874 | 14.0 | 770 | 1.4314 | 0.1322 | -0.0231 | 0.4028 | 0.7778 |
1.5874 | 15.0 | 825 | 1.3915 | 0.3094 | 0.2541 | 0.4583 | 0.7917 |
1.5874 | 16.0 | 880 | 1.3383 | 0.3143 | 0.3726 | 0.4583 | 0.7917 |
1.5874 | 17.0 | 935 | 1.2967 | 0.1861 | 0.3025 | 0.4583 | 0.7778 |
1.5874 | 18.0 | 990 | 1.3368 | 0.1848 | 0.4152 | 0.4722 | 0.8056 |
0.9758 | 19.0 | 1045 | 1.2081 | 0.2376 | 0.4096 | 0.4861 | 0.8056 |
0.9758 | 20.0 | 1100 | 1.1952 | 0.2625 | 0.4872 | 0.5 | 0.8056 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
- Downloads last month
- 6