metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- xtreme_s
metrics:
- wer
model-index:
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod7
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: xtreme_s
type: xtreme_s
config: fleurs.id_id
split: test
args: fleurs.id_id
metrics:
- name: Wer
type: wer
value: 0.5032929202215237
wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod7
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the xtreme_s dataset. It achieves the following results on the evaluation set:
- Loss: 1.0673
- Wer: 0.5033
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- 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: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 90
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.2829 | 7.79 | 300 | 2.8538 | 1.0 |
| 1.9733 | 15.58 | 600 | 0.8923 | 0.7851 |
| 0.4186 | 23.38 | 900 | 0.8297 | 0.6443 |
| 0.2077 | 31.17 | 1200 | 0.8573 | 0.6011 |
| 0.1535 | 38.96 | 1500 | 0.9490 | 0.5800 |
| 0.1163 | 46.75 | 1800 | 1.0380 | 0.5652 |
| 0.1001 | 54.55 | 2100 | 0.9354 | 0.5417 |
| 0.0845 | 62.34 | 2400 | 1.0226 | 0.5364 |
| 0.0711 | 70.13 | 2700 | 1.0799 | 0.5220 |
| 0.0588 | 77.92 | 3000 | 1.0550 | 0.5050 |
| 0.0492 | 85.71 | 3300 | 1.0673 | 0.5033 |
Framework versions
- Transformers 4.39.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2