update model card README.md

README.md

@@ -16,8 +16,8 @@ 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: 1.1368
-- Accuracy: 0.7286
+- Loss: 1.4966
+- Accuracy: 0.6429
 
 ## Model description
 
@@ -43,23 +43,28 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- num_epochs: 10
+- num_epochs: 15
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.3252        | 1.0   | 175  | 1.2178          | 0.4286   |
-| 1.039         | 2.0   | 350  | 1.0262          | 0.5714   |
-| 0.9232        | 3.0   | 525  | 0.9727          | 0.5714   |
-| 0.8248        | 4.0   | 700  | 1.0025          | 0.5143   |
-| 0.7389        | 5.0   | 875  | 0.9947          | 0.6429   |
-| 0.6253        | 6.0   | 1050 | 1.0144          | 0.6857   |
-| 0.5691        | 7.0   | 1225 | 1.0646          | 0.6714   |
-| 0.5264        | 8.0   | 1400 | 1.2786          | 0.6714   |
-| 0.4535        | 9.0   | 1575 | 1.3532          | 0.6429   |
-| 0.4008        | 10.0  | 1750 | 1.1368          | 0.7286   |
+| 1.3315        | 1.0   | 175  | 1.1984          | 0.3857   |
+| 1.0391        | 2.0   | 350  | 1.0071          | 0.5429   |
+| 0.8973        | 3.0   | 525  | 0.9441          | 0.5857   |
+| 0.8199        | 4.0   | 700  | 0.9984          | 0.5286   |
+| 0.7675        | 5.0   | 875  | 0.9477          | 0.6286   |
+| 0.6446        | 6.0   | 1050 | 1.0956          | 0.6429   |
+| 0.6221        | 7.0   | 1225 | 1.0144          | 0.6286   |
+| 0.5543        | 8.0   | 1400 | 1.2473          | 0.6286   |
+| 0.5095        | 9.0   | 1575 | 1.2690          | 0.6714   |
+| 0.4461        | 10.0  | 1750 | 1.1365          | 0.7286   |
+| 0.3678        | 11.0  | 1925 | 1.2065          | 0.7000   |
+| 0.3184        | 12.0  | 2100 | 1.6990          | 0.6286   |
+| 0.271         | 13.0  | 2275 | 1.5335          | 0.6286   |
+| 0.234         | 14.0  | 2450 | 1.3234          | 0.7143   |
+| 0.2049        | 15.0  | 2625 | 1.4966          | 0.6429   |
 
 
 ### Framework versions