End of training

README.md

@@ -8,7 +8,7 @@ datasets:
 metrics:
 - wer
 model-index:
-- name: whisper-small-clean_6-v3
+- name: whisper-small-clean_6-v4
   results:
   - task:
       name: Automatic Speech Recognition
@@ -19,18 +19,18 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 24.71438563767778
+      value: 24.30636512007461
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# whisper-small-clean_6-v3
+# whisper-small-clean_6-v4
 
 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the lyhourt/clean_6 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2953
-- Wer: 24.7144
+- Loss: 0.2900
+- Wer: 24.3064
 
 ## Model description
 
@@ -56,15 +56,17 @@ 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: 400
+- training_steps: 800
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.1207        | 0.5   | 200  | 0.3080          | 25.4138 |
-| 0.1827        | 1.0   | 400  | 0.2953          | 24.7144 |
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.1207        | 0.5    | 200  | 0.3080          | 25.4138 |
+| 0.1827        | 1.0    | 400  | 0.2953          | 24.7144 |
+| 0.0907        | 1.1342 | 600  | 0.2921          | 24.3413 |
+| 0.0904        | 1.5123 | 800  | 0.2900          | 24.3064 |
 
 
 ### Framework versions