update model card README.md

README.md

@@ -1,10 +1,6 @@
 ---
-language:
-- pa-IN
 license: apache-2.0
 tags:
-- automatic-speech-recognition
-- mozilla-foundation/common_voice_8_0
 - generated_from_trainer
 datasets:
 - common_voice
@@ -18,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # 
 
-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_8_0 - PA-IN dataset.
+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.
 It achieves the following results on the evaluation set:
-- Loss: 1.2441
-- Wer: 0.5351
+- Loss: 1.1375
+- Wer: 0.4998
 
 ## Model description
 
@@ -40,13 +36,13 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.00033
+- learning_rate: 0.0003
 - train_batch_size: 16
 - 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: 1100
+- lr_scheduler_warmup_steps: 1500
 - num_epochs: 100.0
 - mixed_precision_training: Native AMP
 
@@ -54,16 +50,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 3.3931        | 9.26  | 500  | 2.6013          | 0.9914 |
-| 0.3457        | 18.52 | 1000 | 1.0316          | 0.6452 |
-| 0.2118        | 27.78 | 1500 | 1.1182          | 0.6354 |
-| 0.1245        | 37.04 | 2000 | 1.2044          | 0.6296 |
-| 0.1068        | 46.3  | 2500 | 1.1400          | 0.5821 |
-| 0.0806        | 55.56 | 3000 | 1.2010          | 0.5786 |
-| 0.0679        | 64.81 | 3500 | 1.1645          | 0.5465 |
-| 0.0506        | 74.07 | 4000 | 1.2748          | 0.5508 |
-| 0.0397        | 83.33 | 4500 | 1.1869          | 0.5394 |
-| 0.0276        | 92.59 | 5000 | 1.2239          | 0.5390 |
+| 3.5841        | 9.26  | 500  | 3.2514          | 0.9941 |
+| 0.3992        | 18.52 | 1000 | 0.8790          | 0.6107 |
+| 0.2409        | 27.78 | 1500 | 1.0012          | 0.6366 |
+| 0.1447        | 37.04 | 2000 | 1.0167          | 0.6276 |
+| 0.1109        | 46.3  | 2500 | 1.0638          | 0.5653 |
+| 0.0797        | 55.56 | 3000 | 1.1447          | 0.5715 |
+| 0.0636        | 64.81 | 3500 | 1.1503          | 0.5316 |
+| 0.0466        | 74.07 | 4000 | 1.2227          | 0.5386 |
+| 0.0372        | 83.33 | 4500 | 1.1214          | 0.5225 |
+| 0.0239        | 92.59 | 5000 | 1.1375          | 0.4998 |
 
 
 ### Framework versions