metadata
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: test
args: gn
metrics:
- name: Wer
type: wer
value: 43.723554301833566
Common Voice 16
This model is a fine-tuned version of 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: 0.3202
- Wer: 43.7236
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 |
|---|---|---|---|---|
| 0.4174 | 1.0101 | 100 | 0.3535 | 47.6728 |
| 0.3411 | 2.0202 | 200 | 0.3387 | 46.3188 |
| 0.2905 | 3.0303 | 300 | 0.3278 | 45.7546 |
| 0.2591 | 4.0404 | 400 | 0.3214 | 44.6544 |
| 0.251 | 5.0505 | 500 | 0.3202 | 43.7236 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1