update model card README.md

README.md

@@ -1,10 +1,6 @@
 ---
-language:
-- ug
 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. -->
 
 # xls-r-uyghur-cv8
 
-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 - UG 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: 0.2163
-- Wer: 0.3249
+- Loss: 0.2024
+- Wer: 0.3280
 
 ## Model description
 
@@ -41,11 +37,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 8
+- train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 32
+- 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
@@ -54,28 +50,26 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Wer    |
-|:-------------:|:-----:|:-----:|:---------------:|:------:|
-| 3.2914        | 4.85  | 500   | 3.2283          | 1.0    |
-| 3.0068        | 9.71  | 1000  | 2.7939          | 0.9980 |
-| 1.4306        | 14.56 | 1500  | 0.4857          | 0.6314 |
-| 1.2831        | 19.42 | 2000  | 0.3679          | 0.6066 |
-| 1.2065        | 24.27 | 2500  | 0.3303          | 0.5560 |
-| 1.1449        | 29.13 | 3000  | 0.3008          | 0.4690 |
-| 1.0926        | 33.98 | 3500  | 0.2817          | 0.4619 |
-| 1.0635        | 38.83 | 4000  | 0.2665          | 0.4391 |
-| 1.029         | 43.69 | 4500  | 0.2616          | 0.4175 |
-| 1.0064        | 48.54 | 5000  | 0.2468          | 0.4051 |
-| 0.9659        | 53.4  | 5500  | 0.2394          | 0.3860 |
-| 0.9254        | 58.25 | 6000  | 0.2373          | 0.3689 |
-| 0.9209        | 63.11 | 6500  | 0.2347          | 0.3670 |
-| 0.889         | 67.96 | 7000  | 0.2291          | 0.3687 |
-| 0.8859        | 72.82 | 7500  | 0.2272          | 0.3616 |
-| 0.8441        | 77.67 | 8000  | 0.2232          | 0.3538 |
-| 0.8284        | 82.52 | 8500  | 0.2224          | 0.3382 |
-| 0.8142        | 87.38 | 9000  | 0.2193          | 0.3310 |
-| 0.8012        | 92.23 | 9500  | 0.2168          | 0.3276 |
-| 0.7781        | 97.09 | 10000 | 0.2163          | 0.3241 |
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 3.3036        | 5.32  | 500  | 3.2628          | 1.0    |
+| 2.9734        | 10.63 | 1000 | 2.5677          | 0.9980 |
+| 1.3466        | 15.95 | 1500 | 0.4455          | 0.6306 |
+| 1.2424        | 21.28 | 2000 | 0.3603          | 0.5301 |
+| 1.1655        | 26.59 | 2500 | 0.3165          | 0.4740 |
+| 1.1026        | 31.91 | 3000 | 0.2930          | 0.4400 |
+| 1.0655        | 37.23 | 3500 | 0.2675          | 0.4159 |
+| 1.0239        | 42.55 | 4000 | 0.2580          | 0.3913 |
+| 0.9938        | 47.87 | 4500 | 0.2373          | 0.3698 |
+| 0.9655        | 53.19 | 5000 | 0.2379          | 0.3675 |
+| 0.9374        | 58.51 | 5500 | 0.2486          | 0.3795 |
+| 0.9065        | 63.83 | 6000 | 0.2243          | 0.3405 |
+| 0.888         | 69.15 | 6500 | 0.2157          | 0.3277 |
+| 0.8646        | 74.47 | 7000 | 0.2103          | 0.3288 |
+| 0.8602        | 79.78 | 7500 | 0.2088          | 0.3238 |
+| 0.8442        | 85.11 | 8000 | 0.2045          | 0.3266 |
+| 0.8335        | 90.42 | 8500 | 0.2038          | 0.3241 |
+| 0.8288        | 95.74 | 9000 | 0.2024          | 0.3280 |
 
 
 ### Framework versions