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---
library_name: transformers
language:
- eu
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_17_0 eu
type: mozilla-foundation/common_voice_17_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 7.215361500971087
---
<!-- 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-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_17_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1259
- Wer: 7.2154
## 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: 4.375e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2208 | 0.05 | 500 | 0.2592 | 20.6915 |
| 0.1489 | 0.1 | 1000 | 0.1971 | 14.6827 |
| 0.1973 | 0.15 | 1500 | 0.1747 | 12.3777 |
| 0.1353 | 1.0296 | 2000 | 0.1527 | 10.7195 |
| 0.1065 | 1.0796 | 2500 | 0.1456 | 9.8694 |
| 0.106 | 1.1296 | 3000 | 0.1362 | 9.0925 |
| 0.0718 | 2.0092 | 3500 | 0.1326 | 8.5428 |
| 0.0683 | 2.0592 | 4000 | 0.1343 | 8.4851 |
| 0.0482 | 2.1092 | 4500 | 0.1336 | 8.1049 |
| 0.0548 | 2.1592 | 5000 | 0.1316 | 7.9244 |
| 0.0282 | 3.0388 | 5500 | 0.1391 | 7.8182 |
| 0.025 | 3.0888 | 6000 | 0.1425 | 7.9409 |
| 0.0274 | 3.1388 | 6500 | 0.1391 | 7.7311 |
| 0.0155 | 4.0184 | 7000 | 0.1492 | 7.6972 |
| 0.0189 | 4.0684 | 7500 | 0.1517 | 7.6569 |
| 0.0139 | 4.1184 | 8000 | 0.1539 | 7.6267 |
| 0.0141 | 4.1684 | 8500 | 0.1550 | 7.5424 |
| 0.0368 | 5.048 | 9000 | 0.1259 | 7.2154 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.2.dev0
- Tokenizers 0.20.0
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