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# deberta-v3-large-survey-topicality-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: 0.3530
- Krippendorff: 0.9269
- Spearman: 0.9424
- Absolute Agreement: 0.8957
- Agreement Within One: 0.9736

## 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   | 1.9667          | -0.1399      | -0.1408  | 0.2778             | 0.8333               |
| No log        | 2.0   | 100  | 1.9452          | -0.2309      | nan      | 0.3889             | 0.7917               |
| No log        | 3.0   | 150  | 1.9260          | -0.2309      | nan      | 0.3889             | 0.7917               |
| No log        | 4.0   | 200  | 1.9029          | -0.2309      | nan      | 0.3889             | 0.7917               |
| No log        | 5.0   | 250  | 1.7441          | -0.2309      | nan      | 0.3889             | 0.7917               |
| No log        | 6.0   | 300  | 1.7721          | -0.2309      | nan      | 0.3889             | 0.7917               |
| No log        | 7.0   | 350  | 1.7503          | -0.2309      | nan      | 0.3889             | 0.7917               |
| No log        | 8.0   | 400  | 1.8355          | -0.2309      | nan      | 0.3889             | 0.7917               |
| No log        | 9.0   | 450  | 1.8326          | -0.2309      | nan      | 0.3889             | 0.7917               |
| 1.451         | 10.0  | 500  | 1.9358          | -0.2309      | nan      | 0.3889             | 0.7917               |
| 1.451         | 11.0  | 550  | 1.7855          | -0.2075      | 0.0284   | 0.4306             | 0.8056               |
| 1.451         | 12.0  | 600  | 1.9276          | -0.0991      | 0.0074   | 0.3611             | 0.8056               |
| 1.451         | 13.0  | 650  | 2.0400          | -0.1222      | -0.0424  | 0.2639             | 0.8333               |
| 1.451         | 14.0  | 700  | 2.2273          | -0.1194      | 0.0063   | 0.3889             | 0.8056               |
| 1.451         | 15.0  | 750  | 2.0630          | -0.0945      | 0.0631   | 0.4028             | 0.8194               |
| 1.451         | 16.0  | 800  | 2.0924          | -0.1046      | -0.0102  | 0.3611             | 0.8194               |
| 1.451         | 17.0  | 850  | 2.2634          | -0.1220      | -0.0764  | 0.3472             | 0.8194               |
| 1.451         | 18.0  | 900  | 2.1491          | -0.1378      | -0.1092  | 0.3611             | 0.8333               |
| 1.451         | 19.0  | 950  | 2.3943          | -0.0815      | 0.0123   | 0.3472             | 0.8194               |
| 0.6727        | 20.0  | 1000 | 2.5402          | -0.1041      | -0.0399  | 0.375              | 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-topicality-rater", "results": []}]}
transformers pytorch deberta-v2 text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us