---
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- common_voice_16_1
metrics:
- wer
model-index:
- name: openai/whisper-large
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_16_1
      type: common_voice_16_1
      config: eu
      split: test
      args: eu
    metrics:
    - name: Wer
      type: wer
      value: 8.144442707519149
---

<!-- 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. -->

# openai/whisper-large

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4111
- Wer: 8.1444

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 40000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.004         | 10.04  | 1000  | 0.2314          | 10.6603 |
| 0.0028        | 20.08  | 2000  | 0.2480          | 10.2783 |
| 0.0027        | 30.11  | 3000  | 0.2492          | 10.0379 |
| 0.0005        | 40.15  | 4000  | 0.2753          | 9.3784  |
| 0.0016        | 50.19  | 5000  | 0.2489          | 9.3003  |
| 0.0006        | 60.23  | 6000  | 0.2599          | 9.0023  |
| 0.0011        | 70.26  | 7000  | 0.2606          | 8.9378  |
| 0.0005        | 80.3   | 8000  | 0.2723          | 8.9270  |
| 0.0001        | 90.34  | 9000  | 0.2764          | 8.5304  |
| 0.0011        | 100.38 | 10000 | 0.2668          | 8.8977  |
| 0.0001        | 110.41 | 11000 | 0.2856          | 8.3701  |
| 0.0           | 120.45 | 12000 | 0.3045          | 8.2890  |
| 0.0           | 130.49 | 13000 | 0.3149          | 8.2441  |
| 0.0           | 140.53 | 14000 | 0.3241          | 8.2285  |
| 0.0           | 150.56 | 15000 | 0.3336          | 8.2060  |
| 0.0           | 160.6  | 16000 | 0.3433          | 8.1601  |
| 0.0           | 170.64 | 17000 | 0.3537          | 8.1806  |
| 0.0           | 180.68 | 18000 | 0.3634          | 8.1874  |
| 0.0           | 190.72 | 19000 | 0.3738          | 8.1786  |
| 0.0           | 200.75 | 20000 | 0.3848          | 8.2441  |
| 0.0           | 210.79 | 21000 | 0.3952          | 8.2324  |
| 0.0           | 220.83 | 22000 | 0.4030          | 8.2480  |
| 0.0001        | 230.87 | 23000 | 0.2919          | 8.4268  |
| 0.0           | 240.9  | 24000 | 0.3137          | 8.1865  |
| 0.0           | 250.94 | 25000 | 0.3271          | 8.1884  |
| 0.0           | 260.98 | 26000 | 0.3378          | 8.1825  |
| 0.0           | 271.02 | 27000 | 0.3472          | 8.1865  |
| 0.0           | 281.05 | 28000 | 0.3556          | 8.2031  |
| 0.0           | 291.09 | 29000 | 0.3637          | 8.2099  |
| 0.0           | 301.13 | 30000 | 0.3710          | 8.1933  |
| 0.0           | 311.17 | 31000 | 0.3781          | 8.1874  |
| 0.0           | 321.2  | 32000 | 0.3845          | 8.1679  |
| 0.0           | 331.24 | 33000 | 0.3905          | 8.1601  |
| 0.0           | 341.28 | 34000 | 0.3971          | 8.1640  |
| 0.0           | 351.32 | 35000 | 0.4022          | 8.1611  |
| 0.0           | 361.36 | 36000 | 0.4046          | 8.1562  |
| 0.0           | 371.39 | 37000 | 0.4073          | 8.1523  |
| 0.0           | 381.43 | 38000 | 0.4093          | 8.1493  |
| 0.0           | 391.47 | 39000 | 0.4107          | 8.1513  |
| 0.0           | 401.51 | 40000 | 0.4111          | 8.1444  |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1