End of training

README.md

@@ -8,9 +8,22 @@ tags:
 - generated_from_trainer
 datasets:
 - MLCommons/peoples_speech
+metrics:
+- wer
 model-index:
 - name: Fine Tune Whisper on People Speech
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Peoples Speech
+      type: MLCommons/peoples_speech
+      args: 'config: English, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 14.784595300261097
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -19,6 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
 # Fine Tune Whisper on People Speech
 
 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Peoples Speech dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5068
+- Wer: 14.7846
 
 ## Model description
 
@@ -43,12 +59,19 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- num_epochs: 5
+- lr_scheduler_warmup_steps: 50
+- training_steps: 500
 - mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0071        | 2.0   | 100  | 0.5080          | 14.2950 |
+| 0.006         | 4.0   | 200  | 0.4859          | 14.1645 |
+| 0.0012        | 6.0   | 300  | 0.4997          | 14.3603 |
+| 0.0002        | 8.0   | 400  | 0.5017          | 14.4582 |
+| 0.0005        | 10.0  | 500  | 0.5068          | 14.7846 |
 
 
 ### Framework versions

model.safetensors

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runs/Dec09_06-27-02_65fa710fc317/events.out.tfevents.1765261627.65fa710fc317.900.6

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