Update README.md

README.md

@@ -37,8 +37,8 @@ Checkpoint tag is represented in the following format:
 1. The `latent_size` is either 16x16 or 32x32, depends on the neural audio codec used in the dataset.
 2. The training dataset is either `random` or `librispeech`. For `librispeech`, a groupped version can be used, tagged as
     `group_n_m_r_c` (see [LenslessMic Version of Librispeech](https://huggingface.co/datasets/Blinorot/lensless_mic_librispeech)
-    (with 288x288 after group is the sensor image size is not the default 256x256). The version of the model, which is
-    fine-tuned using `train-other` is tagges as `librispeech_other` and `_ft` at the end.
+    (with 288x288 after group if the sensor image size is not the default 256x256). The version of the model, which is
+    fine-tuned using `train-other`, is tagged as `librispeech_other` and `_ft` at the end.
 3. The `loss_function` is usually MSE, SSIM, and Raw SSIM, as in the paper. We also provide checkpoints with only MSE,
    MSE and SSIM, and all three with L1 waveform or Mel Losses.
 4. The reconstruction algorithm: `PSF_Unet4M_U5_Unet4M` is the Learned and R-Learned methods from the paper.