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---
language:
- cs
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper Large-v2 Czech CV11
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 cs
      type: mozilla-foundation/common_voice_11_0
      config: cs
      split: test
      args: cs
    metrics:
    - type: wer
      value: 9.032982817995986
      name: Wer
---

<!-- 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-v2 Czech CV11

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 cs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2062
- Wer: 9.0330

## 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
- gradient_accumulation_steps: 8
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0149        | 4.25  | 1000 | 0.1622          | 10.0403 |
| 0.0027        | 8.51  | 2000 | 0.1848          | 9.5136  |
| 0.0008        | 12.76 | 3000 | 0.1930          | 9.3166  |
| 0.0004        | 17.02 | 4000 | 0.2062          | 9.0330  |
| 0.0003        | 21.28 | 5000 | 0.2131          | 9.0440  |


### Framework versions

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