
<!-- 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-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: 0.9754
- Krippendorff: -0.0424
- Spearman: 0.1432
- Absolute Agreement: 0.6897
- Agreement Within One: 0.7676

## 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   | 1.9660          | -0.7952      | nan      | 0.0278             | 1.0                  |
| No log        | 2.0   | 100  | 1.9587          | -0.7952      | nan      | 0.0278             | 1.0                  |
| No log        | 3.0   | 150  | 1.9548          | -0.7155      | -0.3236  | 0.0278             | 0.9306               |
| No log        | 4.0   | 200  | 2.0047          | -0.7155      | -0.3236  | 0.0278             | 0.9306               |
| No log        | 5.0   | 250  | 2.2550          | -0.3248      | -0.3996  | 0.125              | 0.7361               |
| No log        | 6.0   | 300  | 2.4123          | -0.1335      | -0.1046  | 0.25               | 0.7361               |
| No log        | 7.0   | 350  | 2.4828          | -0.1883      | -0.2324  | 0.2083             | 0.7361               |
| No log        | 8.0   | 400  | 2.4175          | -0.3139      | -0.4086  | 0.125              | 0.7361               |
| No log        | 9.0   | 450  | 2.6742          | -0.1335      | -0.1046  | 0.25               | 0.7361               |
| 1.2917        | 10.0  | 500  | 2.8155          | -0.2880      | nan      | 0.2917             | 0.7222               |
| 1.2917        | 11.0  | 550  | 3.0146          | -0.2880      | nan      | 0.2917             | 0.7222               |
| 1.2917        | 12.0  | 600  | 3.0548          | -0.1729      | -0.1993  | 0.2222             | 0.7361               |
| 1.2917        | 13.0  | 650  | 3.3351          | -0.2880      | nan      | 0.2917             | 0.7222               |
| 1.2917        | 14.0  | 700  | 3.0936          | -0.1883      | -0.2324  | 0.2083             | 0.7361               |
| 1.2917        | 15.0  | 750  | 3.3908          | -0.1335      | -0.1046  | 0.25               | 0.7361               |
| 1.2917        | 16.0  | 800  | 2.3496          | -0.375       | -0.3916  | 0.0833             | 0.7778               |
| 1.2917        | 17.0  | 850  | 3.6256          | -0.1729      | -0.1993  | 0.2222             | 0.7361               |
| 1.2917        | 18.0  | 900  | 3.3170          | -0.2037      | -0.3121  | 0.1528             | 0.7361               |
| 1.2917        | 19.0  | 950  | 3.9354          | -0.2369      | -0.3285  | 0.1528             | 0.7361               |
| 0.7206        | 20.0  | 1000 | 3.6945          | -0.1997      | -0.2613  | 0.1944             | 0.7361               |


### 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-fluency-rater-gpt4", "results": []}]}
transformers pytorch deberta-v2 text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us