Update README.md

examples/pytorch/speech-pretraining/README.md

@@ -114,7 +114,7 @@ The experiment was run on 8 GPU V100 (16 GB RAM each) for 4 days.
 In case you have more than 8 GPUs available for a higher effective `batch_size`,
 it is recommended to increase the `learning_rate` to `0.005` for faster convergence.
 
-The results of this run can be seen [here](https://wandb.ai/patrickvonplaten/test/reports/Wav2Vec2-Base--VmlldzoxMTUyODQ0?accessToken=rg6e8u9yizx964k8q47zctq1m4afpvtn1i3qi9exgdmzip6xwkfzvagfajpzj55n) and the checkpoint pretrained for 120,000 steps can be accessed [here](https://huggingface.co/patrickvonplaten/wav2vec2-base-repro-960h-libri-85k-steps)
+The results of this run can be seen [here](https://wandb.ai/patrickvonplaten/test/reports/Wav2Vec2-Base--VmlldzoxMTUyODQ0?accessToken=rg6e8u9yizx964k8q47zctq1m4afpvtn1i3qi9exgdmzip6xwkfzvagfajpzj55n) and the checkpoint pretrained for 85,000 steps can be accessed [here](https://huggingface.co/patrickvonplaten/wav2vec2-base-repro-960h-libri-85k-steps)
 
 
 ### Large