metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-luo-googlefluers-1hr-v1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: luo_ke
split: test
args: luo_ke
metrics:
- name: Wer
type: wer
value: 0.5023333333333333
wav2vec2-large-xls-r-300m-luo-googlefluers-1hr-v1
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 1.0253
- Wer: 0.5023
- Cer: 0.1370
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: 0.0005
- 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: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 9.2323 | 13.3333 | 100 | 3.2827 | 1.0 | 1.0 |
| 2.9657 | 26.6667 | 200 | 2.8565 | 1.0 | 1.0 |
| 1.8583 | 40.0 | 300 | 0.7909 | 0.6233 | 0.1719 |
| 0.2287 | 53.3333 | 400 | 0.9148 | 0.5632 | 0.1543 |
| 0.1116 | 66.6667 | 500 | 0.9245 | 0.571 | 0.1542 |
| 0.07 | 80.0 | 600 | 1.0463 | 0.5342 | 0.1447 |
| 0.0414 | 93.3333 | 700 | 1.0253 | 0.5023 | 0.1370 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1