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---
language:
- eu
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large-V3 Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 eu
type: mozilla-foundation/common_voice_13_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 10.620114220908098
---
<!-- 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-V3 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_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3803
- Wer: 10.6201
## 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: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0326 | 4.85 | 1000 | 0.2300 | 13.3278 |
| 0.004 | 9.71 | 2000 | 0.2723 | 12.2038 |
| 0.0058 | 14.56 | 3000 | 0.2771 | 12.4246 |
| 0.003 | 19.42 | 4000 | 0.2838 | 12.2119 |
| 0.003 | 24.27 | 5000 | 0.2740 | 11.7704 |
| 0.0014 | 29.13 | 6000 | 0.2936 | 11.5436 |
| 0.0015 | 33.98 | 7000 | 0.2911 | 11.5193 |
| 0.0012 | 38.83 | 8000 | 0.2939 | 11.3674 |
| 0.0009 | 43.69 | 9000 | 0.3039 | 11.4140 |
| 0.0002 | 48.54 | 10000 | 0.3063 | 10.9624 |
| 0.0009 | 53.4 | 11000 | 0.3014 | 11.3350 |
| 0.0011 | 58.25 | 12000 | 0.3052 | 11.0474 |
| 0.0001 | 63.11 | 13000 | 0.3204 | 10.8692 |
| 0.0 | 67.96 | 14000 | 0.3413 | 10.7092 |
| 0.0 | 72.82 | 15000 | 0.3524 | 10.6647 |
| 0.0 | 77.67 | 16000 | 0.3607 | 10.6566 |
| 0.0 | 82.52 | 17000 | 0.3675 | 10.6120 |
| 0.0 | 87.38 | 18000 | 0.3737 | 10.6140 |
| 0.0 | 92.23 | 19000 | 0.3782 | 10.6181 |
| 0.0 | 97.09 | 20000 | 0.3803 | 10.6201 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|