|
--- |
|
language: |
|
- eu |
|
license: apache-2.0 |
|
base_model: openai/whisper-large |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_13_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_13_0 eu |
|
type: mozilla-foundation/common_voice_13_0 |
|
config: eu |
|
split: validation |
|
args: eu |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 13.167704366398677 |
|
--- |
|
|
|
<!-- 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_13_0 eu dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4229 |
|
- Wer: 13.1677 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:-----:|:---------------:|:-------:| |
|
| 0.067 | 5.85 | 1000 | 0.2644 | 15.8677 | |
|
| 0.0123 | 11.7 | 2000 | 0.3077 | 14.6326 | |
|
| 0.0052 | 17.54 | 3000 | 0.3317 | 14.1853 | |
|
| 0.0037 | 23.39 | 4000 | 0.3387 | 14.0885 | |
|
| 0.0026 | 29.24 | 5000 | 0.3559 | 14.2618 | |
|
| 0.0026 | 35.09 | 6000 | 0.3604 | 14.2155 | |
|
| 0.002 | 40.94 | 7000 | 0.3734 | 14.1228 | |
|
| 0.0012 | 46.78 | 8000 | 0.3773 | 14.0301 | |
|
| 0.0012 | 52.63 | 9000 | 0.3802 | 13.9072 | |
|
| 0.0012 | 58.48 | 10000 | 0.3850 | 14.4734 | |
|
| 0.0006 | 64.33 | 11000 | 0.3896 | 13.6513 | |
|
| 0.0011 | 70.18 | 12000 | 0.3981 | 13.6311 | |
|
| 0.001 | 76.02 | 13000 | 0.3947 | 13.5949 | |
|
| 0.0002 | 81.87 | 14000 | 0.4039 | 13.6170 | |
|
| 0.0001 | 87.72 | 15000 | 0.4057 | 13.4579 | |
|
| 0.0008 | 93.57 | 16000 | 0.4119 | 13.2745 | |
|
| 0.0001 | 99.42 | 17000 | 0.4203 | 13.1717 | |
|
| 0.0001 | 105.26 | 18000 | 0.4166 | 13.0972 | |
|
| 0.0001 | 111.11 | 19000 | 0.4243 | 13.0448 | |
|
| 0.0 | 116.96 | 20000 | 0.4229 | 13.1677 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.2.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
