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---
language:
- gl
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 Galician
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 gl
type: mozilla-foundation/common_voice_13_0
config: gl
split: test
args: gl
metrics:
- name: Wer
type: wer
value: 5.008278145695364
---
<!-- 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 Galician
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 gl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2940
- Wer: 5.0083
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0176 | 5.0 | 1000 | 0.1563 | 5.2514 |
| 0.004 | 10.0 | 2000 | 0.1884 | 5.5653 |
| 0.0039 | 15.0 | 3000 | 0.2052 | 5.5377 |
| 0.0033 | 20.0 | 4000 | 0.2054 | 5.2997 |
| 0.0012 | 25.0 | 5000 | 0.2115 | 5.1031 |
| 0.001 | 30.0 | 6000 | 0.2195 | 5.2394 |
| 0.001 | 35.0 | 7000 | 0.2257 | 5.3446 |
| 0.001 | 40.0 | 8000 | 0.2178 | 5.4015 |
| 0.0008 | 45.0 | 9000 | 0.2250 | 5.4705 |
| 0.0008 | 50.0 | 10000 | 0.2320 | 5.2946 |
| 0.0002 | 55.0 | 11000 | 0.2368 | 5.3515 |
| 0.0 | 60.0 | 12000 | 0.2551 | 5.0997 |
| 0.0 | 65.0 | 13000 | 0.2634 | 5.0738 |
| 0.0 | 70.0 | 14000 | 0.2697 | 5.0359 |
| 0.0 | 75.0 | 15000 | 0.2752 | 5.0186 |
| 0.0 | 80.0 | 16000 | 0.2804 | 5.0066 |
| 0.0 | 85.0 | 17000 | 0.2852 | 4.9859 |
| 0.0 | 90.0 | 18000 | 0.2894 | 4.9893 |
| 0.0 | 95.0 | 19000 | 0.2927 | 5.0014 |
| 0.0 | 100.0 | 20000 | 0.2940 | 5.0083 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|