metadata
base_model: facebook/wav2vec2-base
datasets:
- common_voice_13_0
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-vi-colab
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: vi
split: test[:50%]
args: vi
metrics:
- type: wer
value: 1
name: Wer
wav2vec2-large-xls-r-vi-colab
This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 3.4884
- Wer: 1.0
- Cer: 1.0
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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 80
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 9.4752 | 7.1111 | 160 | 4.4992 | 1.0 | 1.0 |
| 4.2035 | 14.2222 | 320 | 3.9228 | 1.0 | 1.0 |
| 3.7611 | 21.3333 | 480 | 3.6584 | 1.0 | 1.0 |
| 3.5825 | 28.4444 | 640 | 3.5584 | 1.0 | 1.0 |
| 3.5044 | 35.5556 | 800 | 3.5285 | 1.0 | 1.0 |
| 3.4669 | 42.6667 | 960 | 3.5226 | 1.0 | 1.0 |
| 3.4382 | 49.7778 | 1120 | 3.5093 | 1.0 | 1.0 |
| 3.4183 | 56.8889 | 1280 | 3.4942 | 1.0 | 1.0 |
| 3.4002 | 64.0 | 1440 | 3.4957 | 1.0 | 1.0 |
| 3.3871 | 71.1111 | 1600 | 3.4896 | 1.0 | 1.0 |
| 3.382 | 78.2222 | 1760 | 3.4884 | 1.0 | 1.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1