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# deberta-v3-base-company-names

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the nbroad/company_names dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0693
- Precision: 0.7740
- Recall: 0.7963
- F1: 0.7850
- Accuracy: 0.9769

## 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: 8e-05
- train_batch_size: 48
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0752        | 1.0   | 2126 | 0.0664          | 0.7416    | 0.7979 | 0.7687 | 0.9757   |
| 0.0484        | 2.0   | 4252 | 0.0652          | 0.7725    | 0.7903 | 0.7813 | 0.9768   |
| 0.0415        | 3.0   | 6378 | 0.0693          | 0.7740    | 0.7963 | 0.7850 | 0.9769   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["nbroad/company_names"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "microsoft/deberta-v3-base", "model-index": [{"name": "deberta-v3-base-company-names", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "nbroad/company_names", "type": "nbroad/company_names"}, "metrics": [{"type": "precision", "value": 0.7739696312364425, "name": "Precision"}, {"type": "recall", "value": 0.7962863774326013, "name": "Recall"}, {"type": "f1", "value": 0.7849694196330357, "name": "F1"}, {"type": "accuracy", "value": 0.9769126125154315, "name": "Accuracy"}]}]}]}
transformers pytorch deberta-v2 token-classification generated_from_trainer dataset:nbroad/company_names base_model:microsoft/deberta-v3-base license:mit model-index autotrain_compatible endpoints_compatible region:us