|
--- |
|
library_name: transformers |
|
language: |
|
- gn |
|
license: apache-2.0 |
|
base_model: glob-asr/wav2vec2-large-xls-r-300m-guarani-small |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_16_1 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Common Voice 16 |
|
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: 49.7001998667555 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# Common Voice 16 |
|
|
|
This model is a fine-tuned version of [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4335 |
|
- Wer: 49.7002 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant_with_warmup |
|
- lr_scheduler_warmup_steps: 3000 |
|
- training_steps: 5000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 1.258 | 0.4955 | 500 | 0.3710 | 53.1646 | |
|
| 0.921 | 0.9911 | 1000 | 0.3282 | 49.2338 | |
|
| 0.7458 | 1.4866 | 1500 | 0.2940 | 46.7022 | |
|
| 0.6763 | 1.9822 | 2000 | 0.2628 | 44.9700 | |
|
| 0.568 | 2.4777 | 2500 | 0.2616 | 43.3711 | |
|
| 0.5414 | 2.9732 | 3000 | 0.2504 | 39.8401 | |
|
| 0.484 | 3.4688 | 3500 | 0.2462 | 41.0393 | |
|
| 0.5281 | 3.9643 | 4000 | 0.3584 | 43.5043 | |
|
| 0.5756 | 4.4599 | 4500 | 0.4220 | 44.3038 | |
|
| 0.721 | 4.9554 | 5000 | 0.4335 | 49.7002 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.1 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
