End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 1.0
+      value: 0.8114393463230672
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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 ml-superb-subset dataset.
 It achieves the following results on the evaluation set:
-- Loss: 3.2130
-- Wer: 1.0
+- Loss: 1.6099
+- Wer: 0.8114
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
+- learning_rate: 0.0003
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -65,20 +65,20 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer |
-|:-------------:|:------:|:----:|:---------------:|:---:|
-| 8.25          | 0.8219 | 30   | 6.0908          | 1.0 |
-| 4.6254        | 1.6438 | 60   | 4.0849          | 1.0 |
-| 3.87          | 2.4658 | 90   | 3.7436          | 1.0 |
-| 3.6415        | 3.2877 | 120  | 3.5797          | 1.0 |
-| 3.502         | 4.1096 | 150  | 3.4716          | 1.0 |
-| 3.3476        | 4.9315 | 180  | 3.3731          | 1.0 |
-| 3.2852        | 5.7534 | 210  | 3.3274          | 1.0 |
-| 3.2806        | 6.5753 | 240  | 3.2766          | 1.0 |
-| 3.1827        | 7.3973 | 270  | 3.2398          | 1.0 |
-| 3.1649        | 8.2192 | 300  | 3.2373          | 1.0 |
-| 3.1544        | 9.0411 | 330  | 3.2119          | 1.0 |
-| 3.1401        | 9.8630 | 360  | 3.2130          | 1.0 |
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 3.1825        | 0.8219 | 30   | 3.2071          | 1.0    |
+| 3.0491        | 1.6438 | 60   | 3.0508          | 1.0    |
+| 2.9717        | 2.4658 | 90   | 3.0385          | 1.0    |
+| 2.93          | 3.2877 | 120  | 2.9222          | 1.0    |
+| 2.6444        | 4.1096 | 150  | 2.3753          | 0.9931 |
+| 2.05          | 4.9315 | 180  | 1.9591          | 0.9868 |
+| 1.6856        | 5.7534 | 210  | 1.7810          | 0.9478 |
+| 1.4182        | 6.5753 | 240  | 1.6843          | 0.8843 |
+| 1.1773        | 7.3973 | 270  | 1.6370          | 0.8554 |
+| 1.0521        | 8.2192 | 300  | 1.5868          | 0.8215 |
+| 0.881         | 9.0411 | 330  | 1.5935          | 0.8202 |
+| 0.7605        | 9.8630 | 360  | 1.6099          | 0.8114 |
 
 
 ### Framework versions