End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 50.0
+      value: 43.02848575712144
 ---
 
 <!-- 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-large-v3](https://huggingface.co/openai/whisper-large-v3) on the NG_word_detect dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1854
-- Wer: 50.0
+- Loss: 0.1601
+- Wer: 43.0285
 
 ## Model description
 
@@ -54,24 +54,39 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 128
-- eval_batch_size: 256
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 5
-- training_steps: 20
+- lr_scheduler_warmup_steps: 50
+- training_steps: 500
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.0335        | 4.0   | 4    | 0.0929          | 54.5455 |
-| 0.0021        | 8.0   | 8    | 0.0973          | 54.5455 |
-| 0.0004        | 12.0  | 12   | 0.1535          | 54.5455 |
-| 0.0003        | 16.0  | 16   | 0.1804          | 50.0    |
-| 0.0002        | 20.0  | 20   | 0.1854          | 50.0    |
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.2387        | 0.1524 | 25   | 0.2262          | 59.5952 |
+| 0.2003        | 0.3049 | 50   | 0.1823          | 50.6747 |
+| 0.1797        | 0.4573 | 75   | 0.1787          | 51.6492 |
+| 0.2083        | 0.6098 | 100  | 0.1732          | 49.1004 |
+| 0.1798        | 0.7622 | 125  | 0.1681          | 46.9265 |
+| 0.136         | 0.9146 | 150  | 0.1684          | 48.6507 |
+| 0.0572        | 1.0671 | 175  | 0.1701          | 47.9760 |
+| 0.0533        | 1.2195 | 200  | 0.1600          | 45.6522 |
+| 0.0735        | 1.3720 | 225  | 0.1644          | 46.4018 |
+| 0.0731        | 1.5244 | 250  | 0.1582          | 45.8771 |
+| 0.0734        | 1.6768 | 275  | 0.1583          | 44.6777 |
+| 0.0714        | 1.8293 | 300  | 0.1552          | 44.1529 |
+| 0.0663        | 1.9817 | 325  | 0.1511          | 44.3778 |
+| 0.0389        | 2.1341 | 350  | 0.1561          | 42.8786 |
+| 0.0143        | 2.2866 | 375  | 0.1618          | 43.7031 |
+| 0.0215        | 2.4390 | 400  | 0.1624          | 43.2534 |
+| 0.0203        | 2.5915 | 425  | 0.1591          | 43.1784 |
+| 0.0309        | 2.7439 | 450  | 0.1617          | 43.3283 |
+| 0.0138        | 2.8963 | 475  | 0.1612          | 43.1034 |
+| 0.0065        | 3.0488 | 500  | 0.1601          | 43.0285 |
 
 
 ### Framework versions