---
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
- generated_from_trainer
datasets:
- FineWebSentences
metrics:
- accuracy
model-index:
- name: Deberta-FineWebEdu
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: FineWebSentences
      type: FineWebSentences
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4905470376215008
---

# Deberta-FineWebEdu

This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the FineWebSentences dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4314
- Accuracy: 0.4905

## Model description

Finetuned on sentences from randomly chosen [HuggingFaceFW/fineweb-edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) entries.

## Intended uses & limitations

To be finetuned on more tasks involving English sentences.

<!-- ## Training and evaluation data -->

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

The evaluation and training losses were similar indicating no overfitting.

### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2