End of training

README.md

@@ -25,7 +25,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 76.7479519908554
+      value: 75.33815964945704
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,8 +35,8 @@ 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 17.0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.1447
-- Wer: 76.7480
+- Loss: 1.2762
+- Wer: 75.3382
 
 ## Model description
 
@@ -63,20 +63,21 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 16
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- training_steps: 1000
+- training_steps: 1500
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch   | Step | Validation Loss | Wer     |
 |:-------------:|:-------:|:----:|:---------------:|:-------:|
-| 0.1231        | 5.5556  | 500  | 0.9345          | 77.2052 |
-| 0.0087        | 11.1111 | 1000 | 1.1447          | 76.7480 |
+| 0.1066        | 5.5556  | 500  | 0.9370          | 76.7003 |
+| 0.0053        | 11.1111 | 1000 | 1.1919          | 74.9571 |
+| 0.0012        | 16.6667 | 1500 | 1.2762          | 75.3382 |
 
 
 ### Framework versions
 
 - Transformers 4.47.0
-- Pytorch 2.5.1+cu121
+- Pytorch 2.4.0
 - Datasets 3.2.0
 - Tokenizers 0.21.0

model.safetensors

@@ -1,3 +1,3 @@
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 size 966995080