
<!-- 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-main_passage_consistency-rater-half-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: 0.3709
- Krippendorff: 0.7891
- Spearman: 0.8055
- Absolute Agreement: 0.9002
- Agreement Within One: 0.9519

## 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   | 52   | 1.9290          | -0.7901      | nan      | 0.0556             | 1.0                  |
| No log        | 2.0   | 104  | 1.9260          | -0.7901      | nan      | 0.0556             | 1.0                  |
| No log        | 3.0   | 156  | 2.2136          | -0.3366      | nan      | 0.1667             | 0.8056               |
| No log        | 4.0   | 208  | 3.0444          | -0.3366      | nan      | 0.1667             | 0.8056               |
| No log        | 5.0   | 260  | 3.3406          | -0.3366      | nan      | 0.1667             | 0.8056               |
| No log        | 6.0   | 312  | 3.6074          | -0.3366      | nan      | 0.1667             | 0.8056               |
| No log        | 7.0   | 364  | 3.6395          | -0.3366      | nan      | 0.1667             | 0.8056               |
| No log        | 8.0   | 416  | 3.5991          | 0.2720       | 0.1638   | 0.1389             | 0.8611               |
| No log        | 9.0   | 468  | 3.7407          | 0.2147       | 0.1298   | 0.1389             | 0.8611               |
| 0.9989        | 10.0  | 520  | 3.8742          | 0.2347       | 0.2208   | 0.1389             | 0.8889               |
| 0.9989        | 11.0  | 572  | 3.7369          | 0.3144       | 0.3601   | 0.1667             | 0.8889               |
| 0.9989        | 12.0  | 624  | 3.9522          | 0.2347       | 0.2208   | 0.1389             | 0.8889               |
| 0.9989        | 13.0  | 676  | 3.4874          | 0.2598       | 0.3174   | 0.1944             | 0.8889               |
| 0.9989        | 14.0  | 728  | 4.1072          | 0.2420       | 0.1444   | 0.1389             | 0.8611               |
| 0.9989        | 15.0  | 780  | 4.6448          | 0.3090       | 0.3144   | 0.1389             | 0.9167               |
| 0.9989        | 16.0  | 832  | 4.2375          | 0.3130       | 0.2379   | 0.1389             | 0.9167               |
| 0.9989        | 17.0  | 884  | 4.4929          | 0.1724       | 0.1068   | 0.1111             | 0.9167               |
| 0.9989        | 18.0  | 936  | 4.2319          | 0.2867       | 0.1237   | 0.1389             | 0.8889               |
| 0.9989        | 19.0  | 988  | 4.3529          | 0.2572       | 0.0514   | 0.1111             | 0.8889               |
| 0.3366        | 20.0  | 1040 | 4.5277          | 0.2274       | 0.0428   | 0.1111             | 0.8611               |


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