Model save

README.md

@@ -3,23 +3,11 @@ license: apache-2.0
 base_model: openai/whisper-base
 tags:
 - generated_from_trainer
-datasets:
-- razhan/common_voice_ckb_16
 metrics:
 - wer
 model-index:
 - name: whisper-base-ckb
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: razhan/common_voice_ckb_16
-      type: razhan/common_voice_ckb_16
-    metrics:
-    - name: Wer
-      type: wer
-      value: 0.2917510463075469
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -27,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # whisper-base-ckb
 
-This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the razhan/common_voice_ckb_16 dataset.
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1420
-- Wer: 0.2918
+- Loss: 0.0641
+- Wer: 0.1262
 
 ## Model description
 
@@ -60,7 +48,7 @@ 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: 200
-- training_steps: 1000
+- training_steps: 2300
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -77,6 +65,19 @@ The following hyperparameters were used during training:
 | 0.1015        | 8.7   | 800  | 0.1489          | 0.3059 |
 | 0.0968        | 9.78  | 900  | 0.1440          | 0.2954 |
 | 0.0939        | 10.87 | 1000 | 0.1420          | 0.2918 |
+| 0.0919        | 11.96 | 1100 | 0.1315          | 0.2742 |
+| 0.0839        | 13.04 | 1200 | 0.1217          | 0.2597 |
+| 0.0713        | 14.13 | 1300 | 0.1132          | 0.2371 |
+| 0.0687        | 15.22 | 1400 | 0.1091          | 0.2372 |
+| 0.0647        | 16.3  | 1500 | 0.1022          | 0.2173 |
+| 0.059         | 17.39 | 1600 | 0.0967          | 0.2043 |
+| 0.0539        | 18.48 | 1700 | 0.0897          | 0.1929 |
+| 0.0518        | 19.57 | 1800 | 0.0827          | 0.1718 |
+| 0.0495        | 20.65 | 1900 | 0.0787          | 0.1667 |
+| 0.0444        | 21.74 | 2000 | 0.0718          | 0.1469 |
+| 0.0392        | 22.83 | 2100 | 0.0671          | 0.1368 |
+| 0.0335        | 23.91 | 2200 | 0.0645          | 0.1263 |
+| 0.0292        | 25.0  | 2300 | 0.0641          | 0.1262 |
 
 
 ### Framework versions