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# deberta-v3-large-survey-main_passage_consistency-rater-gpt4

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3012
- Krippendorff: 0.8426
- Spearman: 0.8656
- Absolute Agreement: 0.9183
- Agreement Within One: 0.9673

## 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   | 2.0918          | -0.8602      | nan      | 0.0139             | 1.0                  |
| No log        | 2.0   | 100  | 2.0792          | -0.8602      | nan      | 0.0139             | 1.0                  |
| No log        | 3.0   | 150  | 1.8791          | -0.0618      | -0.1346  | 0.25               | 0.8472               |
| No log        | 4.0   | 200  | 2.0894          | -0.2303      | nan      | 0.375              | 0.8194               |
| No log        | 5.0   | 250  | 2.4916          | -0.2303      | nan      | 0.375              | 0.8194               |
| No log        | 6.0   | 300  | 2.6486          | -0.2303      | nan      | 0.375              | 0.8194               |
| No log        | 7.0   | 350  | 2.9221          | -0.2303      | nan      | 0.375              | 0.8194               |
| No log        | 8.0   | 400  | 2.9376          | -0.2303      | nan      | 0.375              | 0.8194               |
| No log        | 9.0   | 450  | 3.0675          | -0.2303      | nan      | 0.375              | 0.8194               |
| 1.0223        | 10.0  | 500  | 3.0166          | -0.2303      | nan      | 0.375              | 0.8194               |
| 1.0223        | 11.0  | 550  | 3.3407          | -0.2303      | nan      | 0.375              | 0.8194               |
| 1.0223        | 12.0  | 600  | 3.4897          | 0.1396       | 0.2611   | 0.375              | 0.8472               |
| 1.0223        | 13.0  | 650  | 3.8130          | 0.1396       | 0.2611   | 0.375              | 0.8472               |
| 1.0223        | 14.0  | 700  | 4.0549          | 0.1396       | 0.2611   | 0.375              | 0.8472               |
| 1.0223        | 15.0  | 750  | 4.3384          | -0.2303      | nan      | 0.375              | 0.8194               |
| 1.0223        | 16.0  | 800  | 4.5561          | -0.2303      | nan      | 0.375              | 0.8194               |
| 1.0223        | 17.0  | 850  | 4.4345          | -0.2303      | nan      | 0.375              | 0.8194               |
| 1.0223        | 18.0  | 900  | 4.8191          | -0.1764      | -0.0680  | 0.3611             | 0.8194               |
| 1.0223        | 19.0  | 950  | 4.8287          | -0.2303      | nan      | 0.375              | 0.8194               |
| 0.2678        | 20.0  | 1000 | 4.6614          | -0.1528      | -0.0976  | 0.3472             | 0.8194               |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "deberta-v3-large-survey-main_passage_consistency-rater-gpt4", "results": []}]}
transformers pytorch deberta-v2 text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us