End of training

README.md

@@ -23,13 +23,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Afrispeech-200 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7124
-- Wer Ortho: 0.3024
-- Wer: 0.2440
-- Cer: 0.1063
-- Precision: 0.8586
-- Recall: 0.8637
-- F1: 0.8602
+- Loss: 0.6880
+- Wer Ortho: 0.2755
+- Wer: 0.2202
+- Cer: 0.0998
+- Precision: 0.8628
+- Recall: 0.8622
+- F1: 0.8616
 
 ## Model description
 
@@ -62,11 +62,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    | Cer    | Precision | Recall | F1     |
 |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------:|:------:|:------:|
-| 0.4103        | 0.3175 | 100  | 0.6935          | 0.2838    | 0.2252 | 0.1058 | 0.8593    | 0.8625 | 0.8598 |
-| 0.3745        | 0.6349 | 200  | 0.6894          | 0.2767    | 0.2209 | 0.1035 | 0.8609    | 0.8642 | 0.8617 |
-| 0.354         | 0.9524 | 300  | 0.6920          | 0.2817    | 0.2261 | 0.1061 | 0.8606    | 0.8654 | 0.8619 |
-| 0.2184        | 1.2698 | 400  | 0.7025          | 0.2886    | 0.2306 | 0.1125 | 0.8574    | 0.8596 | 0.8571 |
-| 0.2376        | 1.5873 | 500  | 0.7124          | 0.3024    | 0.2440 | 0.1063 | 0.8586    | 0.8637 | 0.8602 |
+| 0.9241        | 0.4237 | 100  | 0.8794          | 0.2973    | 0.2468 | 0.1060 | 0.8428    | 0.8469 | 0.8443 |
+| 0.7528        | 0.8475 | 200  | 0.7464          | 0.2903    | 0.2354 | 0.1032 | 0.8583    | 0.8593 | 0.8581 |
+| 0.5275        | 1.2712 | 300  | 0.7158          | 0.2778    | 0.2285 | 0.1000 | 0.8619    | 0.8627 | 0.8616 |
+| 0.5686        | 1.6949 | 400  | 0.6956          | 0.2805    | 0.2255 | 0.1021 | 0.8638    | 0.8632 | 0.8626 |
+| 0.3472        | 2.1186 | 500  | 0.6880          | 0.2755    | 0.2202 | 0.0998 | 0.8628    | 0.8622 | 0.8616 |
 
 
 ### Framework versions