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_Prod8
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: 0.42037120191588084
wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod8
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: 0.9283
- Wer: 0.4204
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: 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: 600
- num_epochs: 180
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.7974 | 15.58 | 300 | 2.8438 | 1.0 |
| 1.0661 | 31.17 | 600 | 0.7520 | 0.5781 |
| 0.1697 | 46.75 | 900 | 0.8342 | 0.5181 |
| 0.1081 | 62.34 | 1200 | 0.8508 | 0.5010 |
| 0.0833 | 77.92 | 1500 | 0.9216 | 0.5014 |
| 0.0616 | 93.51 | 1800 | 0.9659 | 0.4859 |
| 0.0463 | 109.09 | 2100 | 0.9606 | 0.4646 |
| 0.0356 | 124.68 | 2400 | 0.9255 | 0.4578 |
| 0.0291 | 140.26 | 2700 | 0.9889 | 0.4503 |
| 0.0218 | 155.84 | 3000 | 0.9336 | 0.4371 |
| 0.0182 | 171.43 | 3300 | 0.9283 | 0.4204 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2