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# Whisper Small Mongolia - Dorjzodovsuren Batjargal

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8256
- Wer: 53.1369

## 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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0312        | 7.94  | 1000 | 0.6400          | 54.0698 |
| 0.0021        | 15.87 | 2000 | 0.7654          | 52.8969 |
| 0.0004        | 23.81 | 3000 | 0.8086          | 53.1042 |
| 0.0003        | 31.75 | 4000 | 0.8256          | 53.1369 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
{"language": ["mn"], "license": "mit", "library_name": "transformers", "datasets": ["mozilla-foundation/common_voice_16_0"], "metrics": ["wer"], "pipeline_tag": "automatic-speech-recognition"}
transformers tensorboard safetensors whisper automatic-speech-recognition mn dataset:mozilla-foundation/common_voice_16_0 license:mit endpoints_compatible region:us