readme: Fine-tuning of `wav2vec2-large-lv60` on 100h of Librispeech training data. Results are a bit worse than those reported in the Appendix in Table 3 of the original [paper](https://arxiv.org/pdf/2006.11477.pdf).
  
  Model was trained on *librispeech-clean-train.100* with following hyper-parameters:
  
  - 2 GPUs Titan RTX
  - Total update steps 17500
  - Batch size per GPU: 16 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 used during training
  
  Check: https://wandb.ai/patrickvonplaten/huggingface/reports/Project-Dashboard--Vmlldzo0OTI0OTc?accessToken=8azw8iyxnbiqd4ytxcgm4hbnfh3x1b2c9l2eyfqfzdqw7l0icreljc9qpx0rkl6f
  
  *Result (WER)* on Librispeech test:
  
  | "clean" | "other" |
  |---|---|
  | 4.0 | 10.3 |