metadata
license: apache-2.0
base_model: pinot/wav2vec2-xls-r-300m-ja-cv-14_4
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: cv-14-rakugo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 0.1156558533145275
cv-14-rakugo
This model is a fine-tuned version of pinot/wav2vec2-xls-r-300m-ja-cv-14_4 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3970
- Wer: 0.1157
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: 0.1
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- 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: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.94 | 2 | 2.2324 | 0.2962 |
| No log | 1.88 | 4 | 0.8925 | 0.2073 |
| No log | 2.82 | 6 | 0.3568 | 0.1269 |
| No log | 3.76 | 8 | 0.3970 | 0.1157 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0