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# deberta-v3-large-model-edit-classifier

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: 0.9102
- Krippendorff: 0.7991
- Accuracy: 0.8571
- Macro F1: 0.8377
- Macro Precision: 0.8426
- Macro Recall: 0.8333
- Micro F1: 0.8571
- Micro Precision: 0.8571
- Micro Recall: 0.8571

## 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 | Accuracy | Macro F1 | Macro Precision | Macro Recall | Micro F1 | Micro Precision | Micro Recall |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|
| No log        | 1.0   | 83   | 1.0596          | -0.2872      | 0.5076   | 0.2245   | 0.1692          | 0.3333       | 0.5076   | 0.5076          | 0.5076       |
| No log        | 2.0   | 166  | 0.9677          | -0.2872      | 0.5076   | 0.2245   | 0.1692          | 0.3333       | 0.5076   | 0.5076          | 0.5076       |
| No log        | 3.0   | 249  | 0.8841          | -0.2872      | 0.5076   | 0.2245   | 0.1692          | 0.3333       | 0.5076   | 0.5076          | 0.5076       |
| No log        | 4.0   | 332  | 0.8515          | -0.2872      | 0.5076   | 0.2245   | 0.1692          | 0.3333       | 0.5076   | 0.5076          | 0.5076       |
| No log        | 5.0   | 415  | 0.8048          | 0.2020       | 0.6140   | 0.5405   | 0.6953          | 0.5634       | 0.6140   | 0.6140          | 0.6140       |
| No log        | 6.0   | 498  | 0.6971          | 0.5211       | 0.7112   | 0.6850   | 0.7512          | 0.7224       | 0.7112   | 0.7112          | 0.7112       |
| 0.9047        | 7.0   | 581  | 0.6050          | 0.6242       | 0.7599   | 0.7236   | 0.7615          | 0.7092       | 0.7599   | 0.7599          | 0.7599       |
| 0.9047        | 8.0   | 664  | 0.4781          | 0.7468       | 0.8116   | 0.7820   | 0.7974          | 0.7747       | 0.8116   | 0.8116          | 0.8116       |
| 0.9047        | 9.0   | 747  | 0.4446          | 0.7413       | 0.8267   | 0.7986   | 0.8219          | 0.8000       | 0.8267   | 0.8267          | 0.8267       |
| 0.9047        | 10.0  | 830  | 0.4541          | 0.7510       | 0.8480   | 0.8261   | 0.8455          | 0.8134       | 0.8480   | 0.8480          | 0.8480       |
| 0.9047        | 11.0  | 913  | 0.4691          | 0.7527       | 0.8419   | 0.8189   | 0.8353          | 0.8069       | 0.8419   | 0.8419          | 0.8419       |
| 0.9047        | 12.0  | 996  | 0.6103          | 0.7107       | 0.8237   | 0.8011   | 0.8170          | 0.8011       | 0.8237   | 0.8237          | 0.8237       |
| 0.4334        | 13.0  | 1079 | 0.5507          | 0.7751       | 0.8511   | 0.8360   | 0.8312          | 0.8423       | 0.8511   | 0.8511          | 0.8511       |
| 0.4334        | 14.0  | 1162 | 0.6642          | 0.7548       | 0.8359   | 0.8168   | 0.8174          | 0.8163       | 0.8359   | 0.8359          | 0.8359       |
| 0.4334        | 15.0  | 1245 | 0.6858          | 0.8054       | 0.8632   | 0.8443   | 0.8454          | 0.8433       | 0.8632   | 0.8632          | 0.8632       |
| 0.4334        | 16.0  | 1328 | 0.8332          | 0.7152       | 0.8176   | 0.8007   | 0.7995          | 0.8025       | 0.8176   | 0.8176          | 0.8176       |
| 0.4334        | 17.0  | 1411 | 0.8105          | 0.7753       | 0.8480   | 0.8308   | 0.8314          | 0.8303       | 0.8480   | 0.8480          | 0.8480       |
| 0.4334        | 18.0  | 1494 | 0.8472          | 0.8009       | 0.8602   | 0.8416   | 0.8454          | 0.8382       | 0.8602   | 0.8602          | 0.8602       |
| 0.1213        | 19.0  | 1577 | 0.9164          | 0.7734       | 0.8450   | 0.8273   | 0.8263          | 0.8283       | 0.8450   | 0.8450          | 0.8450       |
| 0.1213        | 20.0  | 1660 | 0.9102          | 0.7991       | 0.8571   | 0.8377   | 0.8426          | 0.8333       | 0.8571   | 0.8571          | 0.8571       |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "deberta-v3-large-model-edit-classifier", "results": []}]}
transformers pytorch deberta-v2 text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us