End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.3884297520661157
+      value: 0.3665879574970484
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9670
-- Wer Ortho: 0.3825
-- Wer: 0.3884
+- Loss: 0.8624
+- Wer Ortho: 0.3658
+- Wer: 0.3666
 
 ## Model description
 
@@ -54,26 +54,19 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 32
+- train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
+- lr_scheduler_type: constant_with_warmup
 - lr_scheduler_warmup_steps: 50
-- training_steps: 4000
+- training_steps: 500
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
-|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
-| 0.1121        | 35.71  | 500  | 0.7395          | 0.3646    | 0.3660 |
-| 0.0526        | 71.43  | 1000 | 0.8020          | 0.3615    | 0.3619 |
-| 0.0263        | 107.14 | 1500 | 0.8685          | 0.3769    | 0.3790 |
-| 0.0162        | 142.86 | 2000 | 0.9158          | 0.3782    | 0.3825 |
-| 0.0152        | 178.57 | 2500 | 0.9300          | 0.3800    | 0.3831 |
-| 0.0138        | 214.29 | 3000 | 0.9595          | 0.3905    | 0.3926 |
-| 0.0127        | 250.0  | 3500 | 0.9687          | 0.3899    | 0.3949 |
-| 0.0119        | 285.71 | 4000 | 0.9670          | 0.3825    | 0.3884 |
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 0.0001        | 17.24 | 500  | 0.8624          | 0.3658    | 0.3666 |
 
 
 ### Framework versions