update model card README.md

README.md

@@ -1,76 +1,42 @@
 ---
-language: 
-- ur
-
-license: apache-2.0
 tags:
-- automatic-speech-recognition
-- robust-speech-event
+- generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_7_0
-metrics:
-- wer
-- cer
+- common_voice
 model-index:
 - name: wav2vec2-60-urdu
-  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: 59.2  # 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: 32.9  # 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
+  results: []
 ---
-# wav2vec2-large-xlsr-53-urdu
+
+<!-- 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
 
 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:
-- Wer: 0.5921
-- Cer: 0.3288
+- Loss: 8.8609
+- Wer: 0.5948
+- Cer: 0.3176
 
 ## Model description
-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.
+More information needed
+
+## Intended uses & limitations
 
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0003
+- learning_rate: 0.0001
 - train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
@@ -78,20 +44,21 @@ The following hyperparameters were used during training:
 - 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
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 30
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Wer    | Cer    |
-|:-------------:|:-----:|:----:|:------:|:------:|
-| 13.83         | 8.33  | 100  | 0.6611 | 0.3639 |
-| 1.0144        | 16.67 | 200  | 0.6498 | 0.3731 |
-| 0.5801        | 25.0  | 300  | 0.6454 | 0.3767 |
-| 0.3344        | 33.33 | 400  | 0.6349 | 0.3548 |
-| 0.1606        | 41.67 | 500  | 0.6105 | 0.3348 |
-| 0.0974        | 50.0  | 600  | 0.5921 | 0.3288 |
+| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 24.6193       | 4.17  | 50   | 8.8884          | 1.4349 | 0.6538 |
+| 4.0847        | 8.33  | 100  | 8.9820          | 0.8175 | 0.4775 |
+| 2.7909        | 12.5  | 150  | 10.4491         | 0.6559 | 0.4129 |
+| 1.8326        | 16.67 | 200  | 8.7698          | 0.6105 | 0.3530 |
+| 1.2727        | 20.83 | 250  | 8.7352          | 0.6061 | 0.3302 |
+| 1.0649        | 25.0  | 300  | 8.7588          | 0.6079 | 0.3240 |
+| 1.0751        | 29.17 | 350  | 8.8609          | 0.5948 | 0.3176 |
 
 
 ### Framework versions