update model card README.md

README.md

@@ -1,29 +1,12 @@
 ---
-language:
-- ha
 license: apache-2.0
 tags:
-- automatic-speech-recognition
-- mozilla-foundation/common_voice_8_0
 - generated_from_trainer
-- "ha"
-- "robust-speech-event"
 datasets:
 - common_voice
 model-index:
 - name: ''
-  results: 
-  - task: 
-      name: Automatic Speech Recognition 
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 8
-      type: mozilla-foundation/common_voice_8_0
-      args: ha
-    metrics:
-       - name: Test WER
-         type: wer
-         value: 51.80
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +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 - HA 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: 0.4925
-- Wer: 0.5714
+- Loss: 0.5050
+- Wer: 0.5169
 
 ## Model description
 
@@ -53,7 +36,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 7.5e-05
+- learning_rate: 9.6e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -69,15 +52,15 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 3.1674        | 8.33  | 500  | 3.0295          | 1.0    |
-| 2.6987        | 16.66 | 1000 | 2.6878          | 1.0    |
-| 1.3454        | 24.99 | 1500 | 0.6814          | 0.6981 |
-| 1.1227        | 33.33 | 2000 | 0.5791          | 0.6513 |
-| 0.9972        | 41.66 | 2500 | 0.5235          | 0.5718 |
-| 0.9123        | 49.99 | 3000 | 0.5104          | 0.5633 |
-| 0.836         | 58.33 | 3500 | 0.4927          | 0.5580 |
-| 0.7725        | 66.66 | 4000 | 0.5078          | 0.5779 |
-| 0.7297        | 74.99 | 4500 | 0.4939          | 0.5737 |
+| 3.0021        | 8.33  | 500  | 2.9059          | 1.0    |
+| 2.6604        | 16.66 | 1000 | 2.6402          | 0.9892 |
+| 1.2216        | 24.99 | 1500 | 0.6051          | 0.6851 |
+| 1.0754        | 33.33 | 2000 | 0.5408          | 0.6464 |
+| 0.9582        | 41.66 | 2500 | 0.5521          | 0.5935 |
+| 0.8653        | 49.99 | 3000 | 0.5156          | 0.5550 |
+| 0.7867        | 58.33 | 3500 | 0.5439          | 0.5606 |
+| 0.7265        | 66.66 | 4000 | 0.4863          | 0.5255 |
+| 0.6699        | 74.99 | 4500 | 0.5050          | 0.5169 |
 
 
 ### Framework versions