transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer mn dataset:mozilla-foundation/common_voice_16_1 dataset:google/fleurs base_model:openai/whisper-large-v3 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- mn
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Large MN - Ankhbayasgalan Davaadorj
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.1 & FLEURS
      type: mozilla-foundation/common_voice_16_1
      config: mn
      split: None
      args: 'config: mn, split: test+validation'
    metrics:
    - name: Wer
      type: wer
      value: 37.049667235025574
---

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# Whisper Large MN - Ankhbayasgalan Davaadorj

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 & FLEURS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3245
- Wer: 37.0497

## 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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4691        | 0.3   | 100  | 0.5472          | 57.2191 |
| 0.3191        | 0.6   | 200  | 0.4417          | 49.0237 |
| 0.2677        | 0.9   | 300  | 0.3791          | 43.3530 |
| 0.1486        | 1.2   | 400  | 0.3560          | 40.1188 |
| 0.1387        | 1.5   | 500  | 0.3430          | 37.8912 |
| 0.1396        | 1.8   | 600  | 0.3245          | 37.0497 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
