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---
language:
- eu
license: apache-2.0
base_model: openai/whisper-large
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Large Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_1 eu
type: mozilla-foundation/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. -->
# Whisper Large Basque
This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_16_1 eu 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
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