
<!-- 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_old_facts-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: 0.3911
- Krippendorff: 0.9259
- Spearman: 0.9416
- Absolute Agreement: 0.8802
- Agreement Within One: 0.9343

## 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   | 1.9135          | 0.0331       | 0.0620   | 0.1944             | 0.7639               |
| No log        | 2.0   | 110  | 1.9089          | -0.2254      | nan      | 0.2917             | 0.5556               |
| No log        | 3.0   | 165  | 1.9020          | -0.2254      | nan      | 0.2917             | 0.5556               |
| No log        | 4.0   | 220  | 1.9002          | -0.1927      | -0.1379  | 0.2639             | 0.5833               |
| No log        | 5.0   | 275  | 2.0013          | -0.2851      | -0.0147  | 0.1667             | 0.9028               |
| No log        | 6.0   | 330  | 1.9979          | -0.2985      | -0.0683  | 0.1667             | 0.875                |
| No log        | 7.0   | 385  | 2.0259          | -0.1959      | 0.0825   | 0.2083             | 0.9306               |
| No log        | 8.0   | 440  | 1.8934          | 0.2597       | 0.2421   | 0.2361             | 0.6806               |
| No log        | 9.0   | 495  | 1.8360          | 0.2956       | 0.3313   | 0.25               | 0.7222               |
| 1.7262        | 10.0  | 550  | 1.7921          | 0.3751       | 0.4065   | 0.3333             | 0.7639               |
| 1.7262        | 11.0  | 605  | 1.7312          | 0.4620       | 0.4217   | 0.3472             | 0.75                 |
| 1.7262        | 12.0  | 660  | 1.7035          | 0.4364       | 0.4636   | 0.3194             | 0.7083               |
| 1.7262        | 13.0  | 715  | 1.7118          | 0.3978       | 0.4790   | 0.375              | 0.6528               |
| 1.7262        | 14.0  | 770  | 1.6110          | 0.5927       | 0.6020   | 0.4306             | 0.7778               |
| 1.7262        | 15.0  | 825  | 1.6626          | 0.4402       | 0.4920   | 0.4028             | 0.6944               |
| 1.7262        | 16.0  | 880  | 1.6148          | 0.5882       | 0.6199   | 0.375              | 0.7917               |
| 1.7262        | 17.0  | 935  | 1.6236          | 0.5597       | 0.6186   | 0.4167             | 0.75                 |
| 1.7262        | 18.0  | 990  | 1.6352          | 0.4110       | 0.4575   | 0.3611             | 0.7222               |
| 1.0082        | 19.0  | 1045 | 1.5764          | 0.4562       | 0.5757   | 0.4028             | 0.6944               |
| 1.0082        | 20.0  | 1100 | 1.5087          | 0.5681       | 0.6098   | 0.4444             | 0.7639               |


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