update model card README.md

README.md

@@ -1,58 +1,11 @@
 ---
-language: 
-- ur
-
-license: apache-2.0
 tags:
-- automatic-speech-recognition
-- robust-speech-event
+- generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_8_0
-metrics:
-- wer
-- cer
+- common_voice
 model-index:
-- name: wav2vec2-urdu-V8-Abid
-  results:
-  - task: 
-      type: automatic-speech-recognition  # Required. Example: automatic-speech-recognition
-      name: Speech Recognition  # Optional. Example: Speech Recognition
-    dataset:
-      type: mozilla-foundation/common_voice_8_0  # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: Common Voice ur  # Required. Example: Common Voice zh-CN
-      args: ur         # Optional. Example: zh-CN
-    metrics:
-      - type: wer    # Required. Example: wer
-        value: 39.52 # Required. Example: 20.90
-        name: Test WER    # Optional. Example: Test WER
-        args: 
-        - learning_rate: 0.00007
-        - train_batch_size: 64
-        - eval_batch_size: 8
-        - seed: 42
-        - gradient_accumulation_steps: 4
-        - total_train_batch_size: 128
-        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-        - lr_scheduler_type: linear
-        - lr_scheduler_warmup_steps: 100
-        - num_epochs: 100
-        - mixed_precision_training: Native AMP        # Optional. Example for BLEU: max_order
-      - type: cer    # Required. Example: wer
-        value: 17.60  # Required. Example: 20.90
-        name: Test CER    # Optional. Example: Test WER
-        args: 
-        - learning_rate: 0.00007
-        - train_batch_size: 64
-        - eval_batch_size: 8
-        - seed: 42
-        - gradient_accumulation_steps: 4
-        - total_train_batch_size: 128
-        - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-        - lr_scheduler_type: linear
-        - lr_scheduler_warmup_steps: 100
-        - num_epochs: 100
-        - mixed_precision_training: Native AMP
-
+- name: wav2vec2-60-Urdu-V8
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -60,45 +13,56 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wav2vec2-60-Urdu-V8
 
-This model is a fine-tuned version of [kingabzpro/wav2vec2-urdu](https://huggingface.co/kingabzpro/wav2vec2-urdu) on the common_voice dataset.
+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: 4.9192
-- Wer: 0.4741
-- Cer: 0.2504
+- Loss: 11.4832
+- Wer: 0.5729
+- Cer: 0.3170
+
+## Model description
+
+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: 7e-05
-- train_batch_size: 64
+- learning_rate: 7.5e-05
+- train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 256
+- 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: 100
-- num_epochs: 100
+- lr_scheduler_warmup_steps: 200
+- num_epochs: 50
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
-| 2.8836        | 16.62 | 50   | 4.7827          | 0.5011 | 0.2625 |
-| 0.6992        | 33.31 | 100  | 3.5358          | 0.4882 | 0.2537 |
-| 0.6321        | 49.92 | 150  | 4.9054          | 0.4774 | 0.2519 |
-| 0.4669        | 66.62 | 200  | 5.9508          | 0.4719 | 0.2513 |
-| 0.3119        | 83.31 | 250  | 5.5791          | 0.4745 | 0.2508 |
-| 0.2788        | 99.92 | 300  | 4.9192          | 0.4741 | 0.2504 |
+| 19.671        | 8.33  | 100  | 7.7671          | 0.8795 | 0.4492 |
+| 2.085         | 16.67 | 200  | 9.2759          | 0.6201 | 0.3320 |
+| 0.6633        | 25.0  | 300  | 8.7025          | 0.5738 | 0.3104 |
+| 0.388         | 33.33 | 400  | 10.2286         | 0.5852 | 0.3128 |
+| 0.2822        | 41.67 | 500  | 11.1953         | 0.5738 | 0.3174 |
+| 0.2293        | 50.0  | 600  | 11.4832         | 0.5729 | 0.3170 |
 
 
 ### Framework versions
 
-- Transformers 4.17.0.dev0
-- Pytorch 1.10.2+cu102
-- Datasets 1.18.2.dev0
+- Transformers 4.16.2
+- Pytorch 1.10.0+cu111
+- Datasets 1.18.3
 - Tokenizers 0.11.0