---
license: apache-2.0
tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  - bayartsogt/ulaanbal-v0
  - bayartsogt/youtube-mongolian-v1
metrics:
  - wer
  - cer
model-index:
  - name: whisper-small-mn-8-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: 26.518461874590344
          - name: Cer
            type: cer
            value: 9.46811616603981
---

<!-- 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-small-mn-8

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2421
- Wer: 26.5185
- Cer: 9.4681

## 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: 32
- 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.3717        | 0.35  | 1000  | 0.4004          | 46.9576 | 16.9664 |
| 0.286         | 0.69  | 2000  | 0.3129          | 37.3935 | 13.5504 |
| 0.2287        | 1.04  | 3000  | 0.2768          | 33.1931 | 11.7806 |
| 0.2257        | 1.39  | 4000  | 0.2590          | 30.7243 | 11.0232 |
| 0.2029        | 1.73  | 5000  | 0.2428          | 29.2003 | 10.4144 |
| 0.1691        | 2.08  | 6000  | 0.2408          | 28.4357 | 10.0306 |
| 0.1626        | 2.43  | 7000  | 0.2369          | 28.0588 | 10.0486 |
| 0.1588        | 2.77  | 8000  | 0.2321          | 27.2340 | 9.6819  |
| 0.1271        | 3.12  | 9000  | 0.2349          | 26.8407 | 9.5574  |
| 0.1263        | 3.47  | 10000 | 0.2356          | 27.1630 | 9.6519  |
| 0.1314        | 3.81  | 11000 | 0.2340          | 26.5567 | 9.4278  |
| 0.1062        | 4.16  | 12000 | 0.2390          | 26.6332 | 9.5162  |
| 0.1081        | 4.5   | 13000 | 0.2398          | 26.5840 | 9.5085  |
| 0.1033        | 4.85  | 14000 | 0.2402          | 26.7096 | 9.4801  |
| 0.097         | 5.2   | 15000 | 0.2421          | 26.5185 | 9.4681  |


### Framework versions

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