---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- honzapucalek/hc_train_v3_independent_v2
metrics:
- wer
model-index:
- name: hc-train-v3-independent-v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: honzapucalek/hc_train_v3_independent_v2 cs
      type: honzapucalek/hc_train_v3_independent_v2
      config: cs
      split: test
      args: cs
    metrics:
    - name: Wer
      type: wer
      value: 0.1169068862960421
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hc-train-v3-independent-v2

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the honzapucalek/hc_train_v3_independent_v2 cs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3728
- Wer: 0.1169

## 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: 2
- total_train_batch_size: 16
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0079        | 13.51 | 1000 | 0.2854          | 0.1256 |
| 0.0037        | 27.03 | 2000 | 0.3198          | 0.1373 |
| 0.0002        | 40.54 | 3000 | 0.3459          | 0.1177 |
| 0.0001        | 54.05 | 4000 | 0.3650          | 0.1168 |
| 0.0001        | 67.57 | 5000 | 0.3728          | 0.1169 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1