metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-vietnamese-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: vi
split: test
args: vi
metrics:
- name: Wer
type: wer
value: 0.7769337016574586
wav2vec2-large-xls-r-300m-vietnamese-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 1.6183
- Wer: 0.7769
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 17.3239 | 3.77 | 50 | 8.2850 | 1.0 |
| 4.8101 | 7.55 | 100 | 3.6457 | 1.0 |
| 3.555 | 11.32 | 150 | 3.5135 | 1.0 |
| 3.4525 | 15.09 | 200 | 3.5400 | 1.0 |
| 3.4141 | 18.87 | 250 | 3.4720 | 1.0 |
| 3.3671 | 22.64 | 300 | 3.4015 | 1.0 |
| 3.1574 | 26.42 | 350 | 3.0054 | 1.0007 |
| 2.4479 | 30.19 | 400 | 2.3789 | 0.9876 |
| 1.5488 | 33.96 | 450 | 1.9272 | 0.9026 |
| 0.9813 | 37.74 | 500 | 1.7429 | 0.8419 |
| 0.7087 | 41.51 | 550 | 1.6931 | 0.8115 |
| 0.5322 | 45.28 | 600 | 1.6583 | 0.7894 |
| 0.4502 | 49.06 | 650 | 1.6183 | 0.7769 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.10.0+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2