---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
datasets:
- conll2003
model-index:
- name: deberta-v3-base_conll03
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deberta-v3-base_conll03

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- F1-type-match: 0.9316
- F1-partial: 0.9733
- F1-strict: 0.9235
- F1-exact: 0.9651

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1-type-match | F1-partial | F1-strict | F1-exact |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:---------:|:--------:|
| 0.0963        | 1.0   | 439  | 0.0814          | 0.8408        | 0.8897     | 0.8323    | 0.8809   |
| 0.0197        | 2.0   | 878  | 0.0803          | 0.9219        | 0.9725     | 0.9138    | 0.9648   |
| 0.0108        | 3.0   | 1317 | 0.0858          | 0.9307        | 0.9728     | 0.9228    | 0.9648   |
| 0.0054        | 4.0   | 1756 | 0.0922          | 0.9313        | 0.9725     | 0.9235    | 0.9643   |
| 0.0033        | 5.0   | 2195 | 0.0973          | 0.9316        | 0.9733     | 0.9235    | 0.9651   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0