update model card README.md

README.md

@@ -1,10 +1,6 @@
 ---
-language:
-- ar
 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-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - AR dataset.
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9694
-- Wer: 0.7824
+- Loss: 1.5476
+- Wer: 0.9696
 
 ## Model description
 
@@ -40,15 +36,15 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.00015
+- learning_rate: 6.5e-05
 - train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 2000
+- lr_scheduler_warmup_steps: 500
 - num_epochs: 10.0
 - mixed_precision_training: Native AMP
 
@@ -56,11 +52,17 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 2.0846        | 1.68  | 500  | 1.1641          | 0.8072 |
-| 2.1201        | 3.35  | 1000 | 1.1776          | 0.8329 |
-| 2.1972        | 5.03  | 1500 | 1.2632          | 0.8724 |
-| 2.2643        | 6.71  | 2000 | 1.3723          | 0.8983 |
-| 2.1649        | 8.39  | 2500 | 1.2550          | 0.8842 |
+| 2.6638        | 0.84  | 500  | 2.3852          | 0.9974 |
+| 2.6578        | 1.67  | 1000 | 2.2796          | 0.9971 |
+| 2.6016        | 2.51  | 1500 | 2.0046          | 0.9961 |
+| 2.5752        | 3.35  | 2000 | 1.9606          | 0.9961 |
+| 2.539         | 4.19  | 2500 | 1.8836          | 0.9940 |
+| 2.5214        | 5.03  | 3000 | 1.8593          | 0.9933 |
+| 2.4684        | 5.86  | 3500 | 1.7816          | 0.9885 |
+| 2.4134        | 6.7   | 4000 | 1.7168          | 0.9808 |
+| 2.3732        | 7.54  | 4500 | 1.6406          | 0.9764 |
+| 2.3371        | 8.37  | 5000 | 1.6087          | 0.9739 |
+| 2.2824        | 9.21  | 5500 | 1.5476          | 0.9696 |
 
 
 ### Framework versions