---
license: cc-by-nc-4.0
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: deberta-base-azerbaijani-v2
  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-base-azerbaijani-v2

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on a various cleaned community corpus. It achieves the following results on the evaluation set:
- Loss: 0.9572

We thank Microsoft Accelerating Foundation Models Research Program for supporting our research.
Authors: Mammad Hajili, Duygu Ataman

## Model description

The model was trained on masked language model task on a 4 X A100 80GB GPU for 23 hours. For downstream tasks, it requires to be fine-tuned based on objective of the task.

## Training and evaluation data

The training data is clean mix of various Azerbaijani corpus shared by the community.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

Perplexity at epoch 5: 2.6

### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1