update readme

README.md

@@ -1,12 +1,28 @@
 ---
+language:
+- ba
 license: apache-2.0
 tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_7_0
 - generated_from_trainer
+- robust-speech-event
 datasets:
 - common_voice
 model-index:
 - name: wav2vec2-large-xls-r-300m-bashkir-cv7_opt
-  results: []
+  results:
+  - task: 
+      name: Automatic Speech Recognition 
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 7
+      type: mozilla-foundation/common_voice_7_0
+      args: ba
+    metrics:
+       - name: Test WER
+         type: wer
+         value: 9.46
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -14,7 +30,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wav2vec2-large-xls-r-300m-bashkir-cv7_opt
 
-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.
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - BA dataset.
+It achieves the following results on the evaluation set:
+- Training Loss: 0.313700
+- Validation Loss: 0.120663
+- Wer: 0.094649
+
 
 ## Model description
 
@@ -42,12 +63,12 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 300
-- num_epochs: 100
+- num_epochs: 50
 - mixed_precision_training: Native AMP
 
 ### Framework versions
 
-- Transformers 4.11.3
+- Transformers 4.16.1
 - Pytorch 1.10.0+cu113
-- Datasets 1.16.2.dev0
+- Datasets 1.18.2
 - Tokenizers 0.10.3