pytorch wav2vec2 transformers
.gitattributes README.md config.json preprocessor_config.json pytorch_model.bin
Second fine-tuning try of `wav2vec2-base`. Results are similar to the ones reported in https://huggingface.co/facebook/wav2vec2-base-100h.

Model was trained on *librispeech-clean-train.100* with following hyper-parameters:

- 2 GPUs Titan RTX
- Total update steps 11000
- Batch size per GPU: 32 corresponding to a *total batch size* of ca. ~750 seconds
- Adam with linear decaying learning rate with 3000 warmup steps
- dynamic padding for batch
- fp16
- attention_mask was **not** used during training

Check: https://wandb.ai/patrickvonplaten/huggingface/runs/1yrpescx?workspace=user-patrickvonplaten

*Result (WER)* on Librispeech:

| "clean" (% rel difference to results in paper) | "other" (% rel difference to results in paper) |
|---|---|
| 6.2 (-1.6%) | 15.2 (-11.2%)|