metadata
tags:
- generated_from_trainer
datasets:
- ml-superb-subset
metrics:
- wer
model-index:
- name: fine-tune-wav2vec2-large-xls-r-300m-xty_224s
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ml-superb-subset
type: ml-superb-subset
config: xty
split: test[:100]
args: xty
metrics:
- name: Wer
type: wer
value: 1.0584538026398491
fine-tune-wav2vec2-large-xls-r-300m-xty_224s
This model was trained from scratch on the ml-superb-subset dataset. It achieves the following results on the evaluation set:
- Loss: 0.7658
- Wer: 1.0585
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.5419 | 5.5172 | 400 | 0.4368 | 0.9994 |
| 0.423 | 11.0345 | 800 | 0.4315 | 1.0 |
| 0.3795 | 16.5517 | 1200 | 0.3892 | 1.0151 |
| 0.3306 | 22.0690 | 1600 | 0.4055 | 1.0013 |
| 0.2464 | 27.5862 | 2000 | 0.4672 | 1.0421 |
| 0.1454 | 33.1034 | 2400 | 0.6656 | 1.0333 |
| 0.0883 | 38.6207 | 2800 | 0.7658 | 1.0585 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1