wav2vec2-base-gumbelVQ-timit-fine-tuned
This model is a fine-tuned version of wav2vec2-pretrained-base-gumbelVQ on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:
- Loss: 0.7549
- Wer: 0.4902
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: 1
- 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: 20.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4628 | 10.0 | 1450 | 0.6779 | 0.5171 |
| 0.3036 | 20.0 | 2900 | 0.7549 | 0.4902 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.3.0.dev20231229+cu118
- Datasets 2.16.0
- Tokenizers 0.15.0
- Downloads last month
- 1
This model does not have enough activity to be deployed to Inference API (serverless) yet.
Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.