
<!-- 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-half

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: 1.4672
- Krippendorff: -0.0771
- Spearman: -0.0511
- Absolute Agreement: 0.3942
- Agreement Within One: 0.7728

## 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   | 1.9959          | 0.0006       | nan      | 0.0                | 0.7222               |
| No log        | 2.0   | 104  | 1.9994          | 0.0006       | nan      | 0.0                | 0.7222               |
| No log        | 3.0   | 156  | 2.0048          | 0.0006       | nan      | 0.0                | 0.7222               |
| No log        | 4.0   | 208  | 2.1527          | -0.1529      | -0.1956  | 0.0                | 0.7222               |
| No log        | 5.0   | 260  | 2.1756          | 0.4828       | 0.4961   | 0.2778             | 0.8611               |
| No log        | 6.0   | 312  | 2.3387          | 0.3497       | 0.3908   | 0.25               | 0.8889               |
| No log        | 7.0   | 364  | 2.4099          | 0.1963       | 0.3202   | 0.1667             | 0.6111               |
| No log        | 8.0   | 416  | 2.3365          | -0.3406      | -0.0159  | 0.1667             | 0.5                  |
| No log        | 9.0   | 468  | 2.4487          | 0.0921       | 0.1069   | 0.1389             | 0.6389               |
| 1.5727        | 10.0  | 520  | 2.2429          | -0.3891      | -0.1081  | 0.1667             | 0.4722               |
| 1.5727        | 11.0  | 572  | 2.3044          | 0.2056       | 0.2241   | 0.1944             | 0.6389               |
| 1.5727        | 12.0  | 624  | 2.3994          | -0.0253      | 0.0152   | 0.1667             | 0.5833               |
| 1.5727        | 13.0  | 676  | 2.3740          | 0.1992       | 0.2342   | 0.1944             | 0.6389               |
| 1.5727        | 14.0  | 728  | 2.4241          | 0.0649       | 0.0877   | 0.1944             | 0.6111               |
| 1.5727        | 15.0  | 780  | 2.4927          | 0.1692       | 0.2025   | 0.1944             | 0.6111               |
| 1.5727        | 16.0  | 832  | 2.6452          | 0.1064       | 0.0628   | 0.1389             | 0.6389               |
| 1.5727        | 17.0  | 884  | 2.6508          | 0.2656       | 0.2242   | 0.1667             | 0.6667               |
| 1.5727        | 18.0  | 936  | 2.6776          | 0.3769       | 0.3329   | 0.25               | 0.7222               |
| 1.5727        | 19.0  | 988  | 2.8348          | 0.2387       | 0.2217   | 0.1944             | 0.6667               |
| 0.9048        | 20.0  | 1040 | 2.8484          | 0.1874       | 0.1557   | 0.1667             | 0.6667               |


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