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deberta-v3-large-survey-fluency-rater
domenicrosati/deberta-v3-large-survey-fluency-rater
deberta-v3-large-survey-fluency-rater is a text classification model from domenicrosati. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Nov 15, 2023
- Updated
- Nov 15, 2023
- SHA
- d440309a
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
deberta-v3-large-survey-fluency-rater
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: 1.3349
- Krippendorff: 0.4934
- Spearman: 0.5298
- Absolute Agreement: 0.4862
- Agreement Within One: 0.8631
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 | 50 | 1.9418 | -0.2790 | -0.0817 | 0.0417 | 0.9306 |
| No log | 2.0 | 100 | 1.9563 | -0.3968 | -0.3236 | 0.0417 | 0.8889 |
| No log | 3.0 | 150 | 1.9360 | -0.2790 | -0.0817 | 0.0417 | 0.9306 |
| No log | 4.0 | 200 | 1.9826 | -0.3968 | -0.3236 | 0.0417 | 0.8889 |
| No log | 5.0 | 250 | 1.9908 | -0.3665 | -0.3871 | 0.0556 | 0.7917 |
| No log | 6.0 | 300 | 1.8144 | -0.2888 | -0.1075 | 0.2778 | 0.7222 |
| No log | 7.0 | 350 | 1.9314 | -0.1378 | -0.0729 | 0.2639 | 0.75 |
| No log | 8.0 | 400 | 2.0468 | -0.3631 | -0.3911 | 0.1389 | 0.75 |
| No log | 9.0 | 450 | 2.0021 | -0.1594 | -0.1099 | 0.25 | 0.7639 |
| 1.536 | 10.0 | 500 | 2.0445 | -0.2759 | -0.1253 | 0.2639 | 0.7222 |
| 1.536 | 11.0 | 550 | 1.9957 | -0.1583 | -0.1012 | 0.2361 | 0.7917 |
| 1.536 | 12.0 | 600 | 2.0293 | -0.2232 | -0.1460 | 0.25 | 0.7639 |
| 1.536 | 13.0 | 650 | 2.0920 | -0.2296 | -0.2063 | 0.1667 | 0.8056 |
| 1.536 | 14.0 | 700 | 2.2456 | -0.2580 | -0.3090 | 0.2083 | 0.75 |
| 1.536 | 15.0 | 750 | 2.2635 | -0.1791 | -0.1913 | 0.2778 | 0.75 |
| 1.536 | 16.0 | 800 | 2.4517 | -0.1779 | -0.2208 | 0.25 | 0.7639 |
| 1.536 | 17.0 | 850 | 2.5741 | -0.2354 | -0.3037 | 0.2361 | 0.7361 |
| 1.536 | 18.0 | 900 | 2.6429 | -0.1990 | -0.2052 | 0.2361 | 0.7639 |
| 1.536 | 19.0 | 950 | 2.8684 | -0.2073 | -0.2513 | 0.1944 | 0.7639 |
| 0.7381 | 20.0 | 1000 | 2.9184 | -0.2585 | -0.2424 | 0.2639 | 0.7361 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Nov 15, 2023
- Updated
- Nov 15, 2023