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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
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