metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-vi-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: vi
split: test
args: vi
metrics:
- name: Wer
type: wer
value: 0.6686410003290556
wav2vec2-large-xls-r-300m-vi-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6916
- Wer: 0.6686
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.495 | 4.6 | 400 | 3.4581 | 1.0 |
| 1.2055 | 9.2 | 800 | 1.6062 | 0.7986 |
| 0.3038 | 13.79 | 1200 | 1.5743 | 0.7307 |
| 0.1831 | 18.39 | 1600 | 1.6441 | 0.7119 |
| 0.1146 | 22.99 | 2000 | 1.6888 | 0.6977 |
| 0.0876 | 27.59 | 2400 | 1.6916 | 0.6686 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2