
<!-- 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-cross_passage_consistency-rater-all

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: 0.8117
- Krippendorff: 0.7331
- Spearman: 0.7616
- Absolute Agreement: 0.7177
- Agreement Within One: 0.9643

## 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   | 1.8836          | -0.0604      | nan      | 0.3472             | 0.7361               |
| No log        | 2.0   | 110  | 1.8656          | -0.0604      | nan      | 0.3472             | 0.7361               |
| No log        | 3.0   | 165  | 1.8291          | -0.0604      | nan      | 0.3472             | 0.7361               |
| No log        | 4.0   | 220  | 1.7616          | -0.2804      | -0.2073  | 0.2917             | 0.6667               |
| No log        | 5.0   | 275  | 1.7034          | -0.2704      | nan      | 0.3194             | 0.6667               |
| No log        | 6.0   | 330  | 1.5944          | -0.2704      | nan      | 0.3194             | 0.6667               |
| No log        | 7.0   | 385  | 1.7482          | -0.2704      | nan      | 0.3194             | 0.6667               |
| No log        | 8.0   | 440  | 1.6018          | -0.2704      | nan      | 0.3194             | 0.6667               |
| No log        | 9.0   | 495  | 1.6257          | -0.2754      | -0.1058  | 0.3194             | 0.6667               |
| 1.6154        | 10.0  | 550  | 1.5990          | -0.2704      | nan      | 0.3194             | 0.6667               |
| 1.6154        | 11.0  | 605  | 1.5314          | -0.0526      | 0.4075   | 0.4306             | 0.6944               |
| 1.6154        | 12.0  | 660  | 1.4840          | 0.0189       | 0.5219   | 0.4722             | 0.7361               |
| 1.6154        | 13.0  | 715  | 1.3873          | 0.0165       | 0.5569   | 0.4861             | 0.7361               |
| 1.6154        | 14.0  | 770  | 1.3236          | 0.4564       | 0.6132   | 0.4722             | 0.875                |
| 1.6154        | 15.0  | 825  | 1.3843          | 0.3405       | 0.5305   | 0.4167             | 0.875                |
| 1.6154        | 16.0  | 880  | 1.2952          | 0.4904       | 0.6072   | 0.4861             | 0.8611               |
| 1.6154        | 17.0  | 935  | 1.3089          | 0.4748       | 0.6265   | 0.4583             | 0.875                |
| 1.6154        | 18.0  | 990  | 1.2532          | 0.4117       | 0.6346   | 0.4861             | 0.8056               |
| 0.9883        | 19.0  | 1045 | 1.2916          | 0.2859       | 0.6616   | 0.5                | 0.7778               |
| 0.9883        | 20.0  | 1100 | 1.2912          | 0.4686       | 0.6283   | 0.4861             | 0.8472               |


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