
<!-- 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-new_fact_related_passage-rater-all-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: 0.4201
- Krippendorff: 0.8827
- Spearman: 0.8845
- Absolute Agreement: 0.8537
- 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   | 1.9465          | 0.0364       | 0.2240   | 0.0556             | 0.8611               |
| No log        | 2.0   | 110  | 1.9474          | 0.0392       | 0.1845   | 0.0556             | 0.7917               |
| No log        | 3.0   | 165  | 1.9468          | -0.0269      | nan      | 0.0278             | 0.7083               |
| No log        | 4.0   | 220  | 1.9454          | -0.0269      | nan      | 0.0278             | 0.7083               |
| No log        | 5.0   | 275  | 1.9541          | -0.0269      | nan      | 0.0278             | 0.7083               |
| No log        | 6.0   | 330  | 1.9415          | 0.1181       | 0.2629   | 0.0972             | 0.8194               |
| No log        | 7.0   | 385  | 1.9009          | 0.2522       | 0.2306   | 0.2361             | 0.7222               |
| No log        | 8.0   | 440  | 1.7945          | 0.1718       | 0.2584   | 0.3194             | 0.6667               |
| No log        | 9.0   | 495  | 1.7244          | 0.1199       | 0.2583   | 0.3611             | 0.6528               |
| 1.4338        | 10.0  | 550  | 1.6929          | 0.2689       | 0.2958   | 0.3194             | 0.7083               |
| 1.4338        | 11.0  | 605  | 1.6008          | 0.5568       | 0.5440   | 0.4306             | 0.8333               |
| 1.4338        | 12.0  | 660  | 1.6055          | 0.2689       | 0.3858   | 0.4028             | 0.6667               |
| 1.4338        | 13.0  | 715  | 1.6136          | 0.1576       | 0.3055   | 0.4028             | 0.6528               |
| 1.4338        | 14.0  | 770  | 1.6585          | 0.5199       | 0.5558   | 0.4583             | 0.8194               |
| 1.4338        | 15.0  | 825  | 1.4875          | 0.4349       | 0.4816   | 0.4306             | 0.7222               |
| 1.4338        | 16.0  | 880  | 1.4030          | 0.4219       | 0.4630   | 0.4722             | 0.75                 |
| 1.4338        | 17.0  | 935  | 1.3910          | 0.5924       | 0.5903   | 0.4722             | 0.8194               |
| 1.4338        | 18.0  | 990  | 1.3350          | 0.5842       | 0.5779   | 0.4861             | 0.8333               |
| 0.7075        | 19.0  | 1045 | 1.4847          | 0.5519       | 0.5815   | 0.375              | 0.7639               |
| 0.7075        | 20.0  | 1100 | 1.3782          | 0.5736       | 0.5788   | 0.4167             | 0.8056               |


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