metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_7_0
metrics:
- wer
base_model: facebook/wav2vec2-base
model-index:
- name: luganda_wav2vec2_ctc_tokenizer
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_7_0
type: common_voice_7_0
config: lg
split: None
args: lg
metrics:
- type: wer
value: 0.5608917697898251
name: Wer
luganda_wav2vec2_ctc_tokenizer
This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_7_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5588
- Wer: 0.5609
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.1365 | 2.4 | 500 | 1.9598 | 1.0 |
| 0.5695 | 4.81 | 1000 | 0.5853 | 0.7329 |
| 0.176 | 7.21 | 1500 | 0.5381 | 0.6747 |
| 0.0845 | 9.62 | 2000 | 0.5128 | 0.6270 |
| 0.0424 | 12.02 | 2500 | 0.4651 | 0.6014 |
| 0.0127 | 14.42 | 3000 | 0.5395 | 0.6049 |
| -0.0063 | 16.83 | 3500 | 0.5169 | 0.5842 |
| -0.0212 | 19.23 | 4000 | 0.4990 | 0.5833 |
| -0.0336 | 21.63 | 4500 | 0.5318 | 0.5680 |
| -0.0424 | 24.04 | 5000 | 0.5465 | 0.5702 |
| -0.0495 | 26.44 | 5500 | 0.5541 | 0.5637 |
| -0.0565 | 28.85 | 6000 | 0.5588 | 0.5609 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2