---
language:
- hy
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-base-hy
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: hy-AM
      split: test
      args: hy-AM
    metrics:
    - name: Wer
      type: wer
      value: 22.36842105263158
---

<!-- 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-large-hy

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2204
- Wer: 22.3684

## 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: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1394        | 5.87  | 400  | 0.1780          | 28.2895 |
| 0.0536        | 11.75 | 800  | 0.1739          | 24.6053 |
| 0.0247        | 17.64 | 1200 | 0.2098          | 22.9605 |
| 0.0154        | 23.52 | 1600 | 0.2035          | 22.1382 |
| 0.0103        | 29.41 | 2000 | 0.2204          | 22.3684 |


### Framework versions

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