transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer hu dataset:mozilla-foundation/common_voice_16_0 base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us
---
datasets:
  - mozilla-foundation/common_voice_16_0
language:
- hu
widget:
  - example_title: Sample 1
    src: >-
      https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac
  - example_title: Sample 2
    src: >-
      https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base Hu v2
  results: []
---

<!-- 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 Base Hu v2

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1599
- Wer Ortho: 12.6641
- Wer: 11.4171 

## 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: 2.75e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 0.199         | 0.33  | 1000  | 0.3838          | 36.7548   | 33.5517 |
| 0.3037        | 0.67  | 2000  | 0.3131          | 31.2748   | 28.3664 |
| 0.221         | 1.0   | 3000  | 0.2546          | 27.1739   | 24.1773 |
| 0.1562        | 1.34  | 4000  | 0.2319          | 23.9341   | 21.3341 |
| 0.1623        | 1.67  | 5000  | 0.2101          | 21.4079   | 18.9623 |
| 0.077         | 2.01  | 6000  | 0.1818          | 18.5415   | 16.2852 |
| 0.078         | 2.34  | 7000  | 0.1846          | 17.8339   | 15.7456 |
| 0.0818        | 2.68  | 8000  | 0.1712          | 16.4669   | 14.5983 |
| 0.0352        | 3.01  | 9000  | 0.1669          | 15.6178   | 14.0676 |
| 0.0413        | 3.35  | 10000 | 0.1673          | 14.9464   | 13.4539 |
| 0.0454        | 3.68  | 11000 | 0.1649          | 14.5459   | 12.7542 |
| 0.0225        | 4.02  | 12000 | 0.1589          | 13.5885   | 12.2087 |
| 0.0269        | 4.35  | 13000 | 0.1638          | 14.3864   | 12.8343 |
| 0.0299        | 4.69  | 14000 | 0.1621          | 13.0555   | 11.7610 |
| 0.0171        | 5.02  | 15000 | 0.1599          | 12.6641   | 11.4171 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
