metadata
language:
- gn
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Common Voice 16 - Guarani
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16
type: mozilla-foundation/common_voice_16_1
config: gn
split: None
args: gn
metrics:
- name: Wer
type: wer
value: 72.71421732886549
Common Voice 16 - Guarani
This model is a fine-tuned version of openai/whisper-base on the Common Voice 16 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6278
- Wer: 72.7142
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.6628 | 0.0573 | 100 | 1.1337 | 94.6146 |
| 1.1593 | 0.1147 | 200 | 0.8508 | 75.5385 |
| 0.9433 | 0.1720 | 300 | 0.7360 | 71.7808 |
| 0.8171 | 0.2294 | 400 | 0.6978 | 66.9459 |
| 0.7444 | 0.2867 | 500 | 0.6278 | 72.7142 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1