End of training

README.md

@@ -6,24 +6,9 @@ tags:
 - generated_from_trainer
 datasets:
 - audiofolder
-metrics:
-- wer
 model-index:
 - name: whisper-small-fr
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: audiofolder
-      type: audiofolder
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Wer
-      type: wer
-      value: 33.80281690140845
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +17,6 @@ should probably proofread and complete it, then remove this comment. -->
 # whisper-small-fr
 
 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the audiofolder dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.4135
-- Wer: 33.8028
 
 ## Model description
 
@@ -59,12 +41,15 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 50
-- training_steps: 100
+- lr_scheduler_warmup_steps: 5
+- training_steps: 10
 - mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| No log        | 10.0  | 10   | 1.0003          | 35.2113 |
 
 
 ### Framework versions