wav2vec2-base-librispeech
This model is a fine-tuned version of facebook/wav2vec2-base on the librispeech_asr_dummy dataset. It achieves the following results on the evaluation set:
- Loss: 0.9548
- Wer: 0.4070
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: 4
- 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: 150
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.4865 | 29.41 | 500 | 3.5010 | 1.0 |
| 1.112 | 58.82 | 1000 | 1.0382 | 0.4767 |
| 0.111 | 88.24 | 1500 | 0.9833 | 0.5116 |
| 0.0438 | 117.65 | 2000 | 0.9302 | 0.4302 |
| 0.0241 | 147.06 | 2500 | 0.9548 | 0.4070 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 104
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for 3funnn/wav2vec2-base-librispeech
Base model
facebook/wav2vec2-base