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# deberta-v3-large-survey-related_passage_old_facts-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: 1.0656
- Krippendorff: 0.7684
- Spearman: 0.8108
- Absolute Agreement: 0.6168
- Agreement Within One: 0.8492

## 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   | 1.9401          | -0.6559      | nan      | 0.0972             | 1.0                  |
| No log        | 2.0   | 100  | 1.9396          | -0.6559      | nan      | 0.0972             | 1.0                  |
| No log        | 3.0   | 150  | 1.9441          | -0.6559      | nan      | 0.0972             | 1.0                  |
| No log        | 4.0   | 200  | 1.9696          | -0.6559      | nan      | 0.0972             | 1.0                  |
| No log        | 5.0   | 250  | 1.9797          | -0.6559      | nan      | 0.0972             | 1.0                  |
| No log        | 6.0   | 300  | 1.9885          | -0.4936      | -0.0607  | 0.0972             | 0.9583               |
| No log        | 7.0   | 350  | 2.0154          | -0.3921      | -0.2733  | 0.1111             | 0.8472               |
| No log        | 8.0   | 400  | 2.0354          | -0.1854      | -0.1735  | 0.1389             | 0.8056               |
| No log        | 9.0   | 450  | 2.1847          | -0.4444      | -0.1842  | 0.125              | 0.9167               |
| 1.6791        | 10.0  | 500  | 2.1343          | -0.1919      | -0.0366  | 0.1667             | 0.875                |
| 1.6791        | 11.0  | 550  | 2.3802          | -0.2199      | 0.0219   | 0.1667             | 0.9028               |
| 1.6791        | 12.0  | 600  | 2.4238          | -0.1432      | 0.0627   | 0.1944             | 0.8889               |
| 1.6791        | 13.0  | 650  | 2.1645          | 0.1016       | 0.2078   | 0.2778             | 0.8194               |
| 1.6791        | 14.0  | 700  | 2.3498          | 0.0959       | 0.2604   | 0.2639             | 0.875                |
| 1.6791        | 15.0  | 750  | 2.4257          | 0.0430       | 0.2141   | 0.2083             | 0.8889               |
| 1.6791        | 16.0  | 800  | 2.6584          | 0.0886       | 0.2120   | 0.1944             | 0.8889               |
| 1.6791        | 17.0  | 850  | 2.8723          | -0.0019      | 0.1364   | 0.1806             | 0.875                |
| 1.6791        | 18.0  | 900  | 2.7402          | 0.0670       | 0.1728   | 0.2222             | 0.8194               |
| 1.6791        | 19.0  | 950  | 3.1369          | -0.0312      | 0.1278   | 0.1528             | 0.8611               |
| 0.8687        | 20.0  | 1000 | 3.2599          | -0.0863      | 0.0656   | 0.2083             | 0.8333               |


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