---
license: apache-2.0
tags:
- whisper-event
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
metrics:
- wer
model-index:
  - name: whisper-medium-mn-4-bayartsogt
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: mn
          split: test
          args:
            language: mn
        metrics:
          - name: Wer
            type: wer
            value: 33.029276818876994
---

<!-- 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. -->

# whisper-medium-mn-4

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6015
- Wer: 33.0293
- Cer: 10.9236

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.0362        | 4.26  | 1000  | 0.4204          | 40.2720 | 13.8389 |
| 0.0087        | 8.51  | 2000  | 0.4712          | 37.4918 | 12.9175 |
| 0.0044        | 12.77 | 3000  | 0.4893          | 36.3393 | 12.4727 |
| 0.0033        | 17.02 | 4000  | 0.5159          | 35.8423 | 12.2933 |
| 0.0017        | 21.28 | 5000  | 0.5183          | 35.2797 | 12.1104 |
| 0.0016        | 25.53 | 6000  | 0.5422          | 35.4326 | 11.7454 |
| 0.0011        | 29.79 | 7000  | 0.5361          | 34.5314 | 11.5196 |
| 0.0004        | 34.04 | 8000  | 0.5406          | 34.0998 | 11.3650 |
| 0.0006        | 38.3  | 9000  | 0.5540          | 33.8650 | 11.2912 |
| 0.0002        | 42.55 | 10000 | 0.5748          | 34.0889 | 11.5333 |
| 0.0003        | 46.81 | 11000 | 0.5771          | 34.5641 | 11.4895 |
| 0.0           | 51.06 | 12000 | 0.5809          | 33.4335 | 11.2070 |
| 0.0           | 55.32 | 13000 | 0.5941          | 33.2095 | 11.0009 |
| 0.0           | 59.57 | 14000 | 0.6015          | 33.0293 | 10.9236 |
| 0.0           | 63.83 | 15000 | 0.6045          | 33.0347 | 10.9125 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2