---
language:
- hu
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 medium Hungarian El Greco
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: hu
      split: test
    metrics:
    - name: Wer
      type: wer
      value: 18.642158316039133
---

<!-- 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 medium Hungarian El Greco

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0,google/fleurs hu,hu_hu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3428
- Wer: 18.6422

## 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: 3e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0621        | 1.05  | 1000  | 0.2690          | 20.5099 |
| 0.0174        | 2.1   | 2000  | 0.2705          | 19.2292 |
| 0.006         | 3.15  | 3000  | 0.2954          | 18.9890 |
| 0.0028        | 4.2   | 4000  | 0.3093          | 18.8023 |
| 0.0016        | 5.25  | 5000  | 0.3240          | 18.9653 |
| 0.0018        | 6.3   | 6000  | 0.3313          | 18.6451 |
| 0.0014        | 7.35  | 7000  | 0.3330          | 18.9446 |
| 0.0016        | 8.39  | 8000  | 0.3428          | 18.6422 |
| 0.0015        | 9.44  | 9000  | 0.3508          | 18.9564 |
| 0.001         | 10.49 | 10000 | 0.3569          | 18.8556 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 2.0.0.dev20221216+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2