metadata
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
metrics:
- wer
model-index:
- name: Wav2Vec2Phoneme-CSfinetune
results: []
Wav2Vec2Phoneme-CSfinetune
This model is a fine-tuned version of facebook/wav2vec2-lv-60-espeak-cv-ft on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7640
- Wer: 0.3064
- Cer: 0.2173
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: 0.0001
- 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: 1000
- num_epochs: 14
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 2.7571 | 2.2805 | 500 | 3.4129 | 0.4619 | 0.3238 |
| 2.0486 | 4.5610 | 1000 | 1.9384 | 0.3985 | 0.2789 |
| 1.7859 | 6.8415 | 1500 | 2.9810 | 0.3588 | 0.2583 |
| 1.505 | 9.1220 | 2000 | 2.2573 | 0.3257 | 0.2305 |
| 1.3879 | 11.4025 | 2500 | 1.7517 | 0.3109 | 0.2206 |
| 1.3334 | 13.6830 | 3000 | 1.7640 | 0.3064 | 0.2173 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.2
- Tokenizers 0.19.1