update model card README.md

README.md

@@ -14,10 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wav2vec2-base-gn-demo
 
-This model is a fine-tuned version of [azuur/wav2vec2-base-gn-demo](https://huggingface.co/azuur/wav2vec2-base-gn-demo) on the common_voice dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.2750
-- Wer: 0.7912
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
 
 ## Model description
 
@@ -37,28 +34,18 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0002
-- train_batch_size: 8
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 300
-- num_epochs: 55
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 30
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.07          | 13.16 | 500  | 1.3797          | 0.8293 |
-| 0.0711        | 26.32 | 1000 | 1.2878          | 0.8277 |
-| 0.0454        | 39.47 | 1500 | 1.2782          | 0.7973 |
-| 0.0281        | 52.63 | 2000 | 1.2750          | 0.7912 |
-
-
 ### Framework versions
 
 - Transformers 4.11.3
-- Pytorch 1.10.0+cu111
+- Pytorch 1.10.2+cu102
 - Datasets 1.18.3
 - Tokenizers 0.10.3