metadata
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: 39.84010659560293
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: 0.2438
- Wer: 39.8401
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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.2579 | 0.4955 | 500 | 0.3710 | 53.4310 |
| 0.919 | 0.9911 | 1000 | 0.3295 | 49.9001 |
| 0.746 | 1.4866 | 1500 | 0.2902 | 45.1033 |
| 0.6767 | 1.9822 | 2000 | 0.2674 | 43.3711 |
| 0.574 | 2.4777 | 2500 | 0.2677 | 42.5716 |
| 0.5485 | 2.9732 | 3000 | 0.2438 | 39.8401 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1