End of training

README.md

@@ -24,7 +24,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 58.291457286432156
+      value: 53.936348408710224
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,8 +34,8 @@ 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 Common Voice 16 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5062
-- Wer: 58.2915
+- Loss: 0.4522
+- Wer: 53.9363
 
 ## Model description
 
@@ -61,17 +61,19 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant_with_warmup
 - lr_scheduler_warmup_steps: 3000
-- training_steps: 2000
+- training_steps: 3000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Wer     |
 |:-------------:|:------:|:----:|:---------------:|:-------:|
-| 2.9797        | 0.4955 | 500  | 1.0523          | 92.2948 |
-| 1.1502        | 0.9911 | 1000 | 0.6757          | 87.0463 |
-| 0.7171        | 1.4866 | 1500 | 0.5723          | 63.7074 |
-| 0.5485        | 1.9822 | 2000 | 0.5062          | 58.2915 |
+| 2.9797        | 0.4955 | 500  | 1.0523          | 91.7365 |
+| 1.1502        | 0.9911 | 1000 | 0.6757          | 87.2138 |
+| 0.717         | 1.4866 | 1500 | 0.5718          | 63.4841 |
+| 0.5485        | 1.9822 | 2000 | 0.5059          | 58.3473 |
+| 0.3345        | 2.4777 | 2500 | 0.4828          | 56.7281 |
+| 0.2748        | 2.9732 | 3000 | 0.4522          | 53.9363 |
 
 
 ### Framework versions