---
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
metrics:
- recall
- precision
model-index:
- name: deberta-v3-xsmall-finetuned-ner-1024
  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-v3-xsmall-finetuned-ner-1024

This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1799
- Recall: 0.0
- Precision: 0.0
- Fbeta Score: nan

## 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: 0.0013
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Recall | Precision | Fbeta Score |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:-----------:|
| 0.1644        | 1.0   | 4496  | 0.1353          | 0.0    | 0.0       | nan         |
| 0.1576        | 2.0   | 8992  | 0.1371          | 0.0    | 0.0       | nan         |
| 0.1728        | 3.0   | 13488 | 0.2194          | 0.0    | 0.0       | nan         |
| 0.1422        | 4.0   | 17984 | 0.1799          | 0.0    | 0.0       | nan         |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.19.1