---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-finetuned-ner-finetuned-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# deberta-finetuned-ner-finetuned-ner

This model is a fine-tuned version of [baptiste/deberta-finetuned-ner](https://huggingface.co/baptiste/deberta-finetuned-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7964
- Precision: 0.6210
- Recall: 0.3188
- F1: 0.4213
- Accuracy: 0.8212

## 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: 2e-05
- 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
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 4    | 1.0763          | 0.5583    | 0.1387 | 0.2222 | 0.7916   |
| No log        | 2.0   | 8    | 0.8910          | 0.8108    | 0.3106 | 0.4491 | 0.8212   |
| No log        | 3.0   | 12   | 0.7964          | 0.6210    | 0.3188 | 0.4213 | 0.8212   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2