update model card README.md

README.md

@@ -1,40 +1,23 @@
 ---
-language:
-- el
 license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
-datasets:
-- mozilla-foundation/common_voice_11_0,google/fleurs
 metrics:
 - wer
 model-index:
-- name: Whisper small Greek Farsipal and  El Greco
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr
-      type: mozilla-foundation/common_voice_11_0,google/fleurs
-      config: el
-      split: None
-    metrics:
-    - name: Wer
-      type: wer
-      value: 16.50260029717682
+- name: emilios/whisper-sm-farsipal-e7
+  results: []
 ---
 
 <!-- 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 Greek Farsipal and  El Greco
+# emilios/whisper-sm-farsipal-e7
 
-This model is a fine-tuned version of [emilios/whisper-sm-farsipal-e7](https://huggingface.co/emilios/whisper-sm-farsipal-e7) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
+This model is a fine-tuned version of [emilios/whisper-sm-farsipal-e7](https://huggingface.co/emilios/whisper-sm-farsipal-e7) on the None dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.5015
-- Wer: 16.5026
+- Wer: 16.5583
 
 ## Model description
 
@@ -53,7 +36,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-09
+- learning_rate: 1e-09
 - train_batch_size: 32
 - eval_batch_size: 16
 - seed: 42
@@ -61,22 +44,17 @@ 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: 500
-- training_steps: 10000
+- training_steps: 5000
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Wer     |
-|:-------------:|:-----:|:-----:|:---------------:|:-------:|
-| 0.0002        | 2.49  | 1000  | 0.5015          | 16.5212 |
-| 0.0002        | 4.98  | 2000  | 0.5015          | 16.5119 |
-| 0.0002        | 7.46  | 3000  | 0.5015          | 16.5397 |
-| 0.0002        | 9.95  | 4000  | 0.5015          | 16.5397 |
-| 0.0002        | 12.44 | 5000  | 0.5015          | 16.5583 |
-| 0.0002        | 14.93 | 6000  | 0.5015          | 16.5769 |
-| 0.0002        | 17.41 | 7000  | 0.5015          | 16.5397 |
-| 0.0002        | 19.9  | 8000  | 0.5015          | 16.5026 |
-| 0.0002        | 22.39 | 9000  | 0.5015          | 16.5212 |
-| 0.0002        | 24.88 | 10000 | 0.5020          | 16.5583 |
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0002        | 2.49  | 1000 | 0.5015          | 16.5119 |
+| 0.0002        | 4.98  | 2000 | 0.5015          | 16.5583 |
+| 0.0002        | 7.46  | 3000 | 0.5015          | 16.4655 |
+| 0.0002        | 9.95  | 4000 | 0.5015          | 16.5119 |
+| 0.0002        | 12.44 | 5000 | 0.5015          | 16.5583 |
 
 
 ### Framework versions