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# deberta-v3-large-survey-new_fact_related_passage-rater

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: 0.2316
- Krippendorff: 0.9171
- Spearman: 0.9146
- Absolute Agreement: 0.9372
- Agreement Within One: 0.9874

## 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   | 50   | 1.9025          | -0.0055      | nan      | 0.0833             | 0.6389               |
| No log        | 2.0   | 100  | 1.9012          | 0.1665       | 0.2932   | 0.1528             | 0.8611               |
| No log        | 3.0   | 150  | 1.9013          | -0.5318      | nan      | 0.1806             | 1.0                  |
| No log        | 4.0   | 200  | 1.9030          | -0.5318      | nan      | 0.1806             | 1.0                  |
| No log        | 5.0   | 250  | 1.9633          | -0.3932      | -0.1362  | 0.1528             | 0.8889               |
| No log        | 6.0   | 300  | 2.1312          | -0.3716      | -0.3587  | 0.0556             | 0.7361               |
| No log        | 7.0   | 350  | 2.1081          | -0.2882      | -0.1942  | 0.1111             | 0.8056               |
| No log        | 8.0   | 400  | 2.0798          | -0.2532      | -0.1339  | 0.1806             | 0.875                |
| No log        | 9.0   | 450  | 2.0693          | -0.2269      | -0.1385  | 0.25               | 0.5694               |
| 1.6529        | 10.0  | 500  | 2.0939          | -0.2456      | -0.2515  | 0.1667             | 0.6667               |
| 1.6529        | 11.0  | 550  | 2.1227          | -0.0758      | 0.0820   | 0.2639             | 0.6111               |
| 1.6529        | 12.0  | 600  | 2.0465          | -0.1802      | 0.0413   | 0.3056             | 0.5694               |
| 1.6529        | 13.0  | 650  | 2.0901          | -0.1164      | -0.0485  | 0.2639             | 0.625                |
| 1.6529        | 14.0  | 700  | 2.1685          | 0.2526       | 0.3009   | 0.2778             | 0.9028               |
| 1.6529        | 15.0  | 750  | 2.1592          | 0.2603       | 0.2661   | 0.3194             | 0.7083               |
| 1.6529        | 16.0  | 800  | 2.3096          | 0.2225       | 0.2235   | 0.2917             | 0.7778               |
| 1.6529        | 17.0  | 850  | 2.2947          | 0.2268       | 0.2128   | 0.3056             | 0.7222               |
| 1.6529        | 18.0  | 900  | 2.3396          | 0.0808       | 0.1413   | 0.3056             | 0.6528               |
| 1.6529        | 19.0  | 950  | 2.6040          | -0.0037      | 0.1140   | 0.3056             | 0.6389               |
| 0.7915        | 20.0  | 1000 | 2.5205          | 0.2986       | 0.2466   | 0.1944             | 0.8194               |


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