---
library_name: transformers
tags:
- whisper-event
- hf-asr-leaderboard
license: mit
datasets:
- mozilla-foundation/common_voice_16_1
language:
- mn
pipeline_tag: automatic-speech-recognition
---

# Model Card for Model ID

GPU - A100-80GB



## Model Details

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.


### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** Ankhbayasgalan Davaadorj
- **Model type:** Whisper
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model:** openai/whisper-large-v3



#### Training Hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-03
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP




### Results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.4856        | 1.97  | 1000  | 0.496397         |
| 0.1312        | 3.94  | 2000  | 0.395565         |



## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** A100 80GB
- **Hours used:** 1:07:08 hours



## Model Card Authors 

@Ankhbayasgalan davaadorj

## Model Card Contact

ankhbayasgaland@gmail.com