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---
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
[email protected] |