Update README.md

README.md

@@ -1,37 +1,71 @@
 ---
+language: 
+- ur
+
+license: apache-2.0
 tags:
-- generated_from_trainer
+- automatic-speech-recognition
+- robust-speech-event
 datasets:
-- common_voice
+- mozilla-foundation/common_voice_7_0
+metrics:
+- wer
+- cer
 model-index:
 - name: wav2vec2-60-urdu
-  results: []
+  results:
+  - task: 
+      type: automatic-speech-recognition  # Required. Example: automatic-speech-recognition
+      name: Urdu Speech Recognition  # Optional. Example: Speech Recognition
+    dataset:
+      type: mozilla-foundation/common_voice_7_0  # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
+      name: Urdu  # Required. Example: Common Voice zh-CN
+      args: ur         # Optional. Example: zh-CN
+    metrics:
+      - type: wer    # Required. Example: wer
+        value: 59.1  # Required. Example: 20.90
+        name: Test WER    # Optional. Example: Test WER
+        args: 
+        - learning_rate: 0.0003
+        - train_batch_size: 16
+        - eval_batch_size: 8
+        - seed: 42
+        - gradient_accumulation_steps: 2
+        - total_train_batch_size: 32
+        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+        - lr_scheduler_type: linear
+        - lr_scheduler_warmup_steps: 200
+        - num_epochs: 50
+        - mixed_precision_training: Native AMP         # Optional. Example for BLEU: max_order
+      - type: cer    # Required. Example: wer
+        value: 33.1  # Required. Example: 20.90
+        name: Test CER    # Optional. Example: Test WER
+        args: 
+        - learning_rate: 0.0003
+        - train_batch_size: 16
+        - eval_batch_size: 8
+        - seed: 42
+        - gradient_accumulation_steps: 2
+        - total_train_batch_size: 32
+        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+        - lr_scheduler_type: linear
+        - lr_scheduler_warmup_steps: 200
+        - num_epochs: 50
+        - mixed_precision_training: Native AMP         # Optional. Example for BLEU: max_order
 ---
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# wav2vec2-60-urdu
+# wav2vec2-large-xlsr-53-urdu
 
 This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-urdu-urm-60](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-urdu-urm-60) on the common_voice dataset.
 It achieves the following results on the evaluation set:
-- Loss: 6.4496
 - Wer: 0.5913
 - Cer: 0.3310
 
 ## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
+The training and valid dataset is 0.58 hours. It was hard to train any model on lower number of so I decided to take vakyansh-wav2vec2-urdu-urm-60 checkpoint and finetune the wav2vec2 model.  
 
 ## Training procedure
+Trained on Harveenchadha/vakyansh-wav2vec2-urdu-urm-60 due to lesser number of samples.
+
 
 ### Training hyperparameters