transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer mn dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-large-v2 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- mn
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper Large Mongolian
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 16.0
      type: mozilla-foundation/common_voice_16_0
      config: mn
      split: None
      args: 'config: mn, split: test'
    metrics:
    - type: wer
      value: 37.23357981731187
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Large Mongolian

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4028
- Wer: 37.2336

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3446        | 0.99  | 1000 | 0.4391          | 51.4572 |
| 0.1481        | 1.98  | 2000 | 0.3765          | 42.2412 |
| 0.076         | 2.97  | 3000 | 0.3830          | 39.0822 |
| 0.0149        | 3.96  | 4000 | 0.4028          | 37.2336 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
