dgx1_w2lm_base_plus_finetune_teacher_noise_libri360_50_epochs_batch_16
This model is a fine-tuned version of patrickvonplaten/wavlm-libri-clean-100h-base-plus on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1396
- Wer: 0.0921
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 256
- total_train_batch_size: 4096
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2792 | 5.91 | 150 | 0.2173 | 0.1413 |
0.1681 | 11.81 | 300 | 0.1653 | 0.1146 |
0.1325 | 17.72 | 450 | 0.1510 | 0.1040 |
0.1148 | 23.63 | 600 | 0.1451 | 0.0992 |
0.1044 | 29.53 | 750 | 0.1418 | 0.0964 |
0.0969 | 35.44 | 900 | 0.1403 | 0.0947 |
0.0924 | 41.35 | 1050 | 0.1403 | 0.0929 |
0.0899 | 47.25 | 1200 | 0.1396 | 0.0921 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1
- Downloads last month
- 7
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.