update model card README.md

README.md

@@ -14,8 +14,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.8646
-- Wer: 0.5194
+- Loss: 1.7585
+- Wer: 0.3809
 
 ## Model description
 
@@ -46,19 +46,36 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 4.1014        | 2.66  | 500  | 2.8445          | 1.0    |
-| 1.9003        | 5.32  | 1000 | 1.3730          | 0.9951 |
-| 1.0625        | 7.98  | 1500 | 1.2459          | 0.6523 |
-| 0.7351        | 10.64 | 2000 | 1.4289          | 0.5867 |
-| 0.569         | 13.3  | 2500 | 1.5404          | 0.5670 |
-| 0.4358        | 15.96 | 3000 | 1.5742          | 0.5644 |
-| 0.3617        | 18.62 | 3500 | 1.6887          | 0.5373 |
-| 0.2985        | 21.28 | 4000 | 1.7297          | 0.5338 |
-| 0.2408        | 23.94 | 4500 | 1.7960          | 0.5202 |
-| 0.2021        | 26.6  | 5000 | 1.8591          | 0.5206 |
-| 0.1857        | 29.26 | 5500 | 1.8646          | 0.5194 |
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 4.0637        | 1.05  | 500   | 2.9155          | 1.0    |
+| 1.8717        | 2.09  | 1000  | 1.3860          | 0.7360 |
+| 1.2162        | 3.14  | 1500  | 1.1553          | 0.5856 |
+| 1.0079        | 4.18  | 2000  | 1.4409          | 0.5260 |
+| 0.8638        | 5.23  | 2500  | 1.0576          | 0.4863 |
+| 0.7614        | 6.28  | 3000  | 1.0726          | 0.4846 |
+| 0.7057        | 7.32  | 3500  | 1.2451          | 0.4555 |
+| 0.6127        | 8.37  | 4000  | 1.2994          | 0.4386 |
+| 0.5773        | 9.41  | 4500  | 1.3738          | 0.4495 |
+| 0.5394        | 10.46 | 5000  | 1.3360          | 0.4443 |
+| 0.509         | 11.51 | 5500  | 1.4233          | 0.4070 |
+| 0.4561        | 12.55 | 6000  | 1.4158          | 0.4088 |
+| 0.4444        | 13.6  | 6500  | 1.5068          | 0.4110 |
+| 0.418         | 14.64 | 7000  | 1.4809          | 0.4146 |
+| 0.4034        | 15.69 | 7500  | 1.5531          | 0.4082 |
+| 0.3623        | 16.74 | 8000  | 1.5302          | 0.4139 |
+| 0.3427        | 17.78 | 8500  | 1.4928          | 0.4055 |
+| 0.3325        | 18.83 | 9000  | 1.5403          | 0.4025 |
+| 0.3159        | 19.87 | 9500  | 1.6301          | 0.3938 |
+| 0.2876        | 20.92 | 10000 | 1.6854          | 0.3985 |
+| 0.2752        | 21.97 | 10500 | 1.6375          | 0.3891 |
+| 0.2585        | 23.01 | 11000 | 1.6425          | 0.3854 |
+| 0.2329        | 24.06 | 11500 | 1.6607          | 0.3907 |
+| 0.2242        | 25.1  | 12000 | 1.7301          | 0.3843 |
+| 0.2015        | 26.15 | 12500 | 1.7208          | 0.3873 |
+| 0.1951        | 27.2  | 13000 | 1.7489          | 0.3779 |
+| 0.181         | 28.24 | 13500 | 1.7578          | 0.3816 |
+| 0.1728        | 29.29 | 14000 | 1.7585          | 0.3809 |
 
 
 ### Framework versions