End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 46.25
+      value: 13.333333333333334
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.1396
-- Wer: 46.25
+- Loss: 0.1798
+- Wer: 13.3333
 
 ## Model description
 
@@ -60,23 +60,23 @@ 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: 50
-- training_steps: 100
+- training_steps: 1000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| No log        | 10.0  | 10   | 4.1585          | 27.5000 |
-| No log        | 20.0  | 20   | 3.0184          | 33.75   |
-| 3.8104        | 30.0  | 30   | 2.1938          | 105.0   |
-| 3.8104        | 40.0  | 40   | 1.4511          | 267.5   |
-| 0.8755        | 50.0  | 50   | 1.3480          | 178.75  |
-| 0.8755        | 60.0  | 60   | 1.2947          | 100.0   |
-| 0.8755        | 70.0  | 70   | 1.2436          | 86.25   |
-| 0.4202        | 80.0  | 80   | 1.1970          | 66.25   |
-| 0.4202        | 90.0  | 90   | 1.1718          | 52.5    |
-| 0.188         | 100.0 | 100  | 1.1396          | 46.25   |
+| Training Loss | Epoch | Step | Validation Loss | Wer      |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6172        | 0.1   | 100  | 0.6200          | 107.3958 |
+| 0.2709        | 0.21  | 200  | 0.3492          | 67.0833  |
+| 0.2839        | 0.31  | 300  | 0.2959          | 40.7292  |
+| 0.2876        | 0.41  | 400  | 0.2766          | 29.5833  |
+| 0.2296        | 0.52  | 500  | 0.2375          | 17.3958  |
+| 0.2649        | 0.62  | 600  | 0.2102          | 15.3125  |
+| 0.2644        | 0.72  | 700  | 0.1957          | 17.3958  |
+| 0.2384        | 0.82  | 800  | 0.1886          | 13.7500  |
+| 0.2325        | 0.93  | 900  | 0.1811          | 13.6458  |
+| 0.1374        | 1.03  | 1000 | 0.1798          | 13.3333  |
 
 
 ### Framework versions