update model card README.md

README.md

@@ -1,41 +1,38 @@
 ---
-language:
-- el
 license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_11_0
+- common_voice_11_0
 metrics:
 - wer
 model-index:
-- name: Whisper medium Greek El Greco
+- name: emilios/whisper-medium-el-n2
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: mozilla-foundation/common_voice_11_0 el
-      type: mozilla-foundation/common_voice_11_0
+      name: common_voice_11_0
+      type: common_voice_11_0
       config: el
       split: test
       args: el
     metrics:
     - name: Wer
       type: wer
-      value: 10.27117384843982
+      value: 9.927563150074294
 ---
 
 <!-- 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 medium Greek El Greco
+# emilios/whisper-medium-el-n2
 
-This model is a fine-tuned version of [emilios/whisper-medium-el-n2](https://huggingface.co/emilios/whisper-medium-el-n2) on the mozilla-foundation/common_voice_11_0 el dataset.
+This model is a fine-tuned version of [emilios/whisper-medium-el-n2](https://huggingface.co/emilios/whisper-medium-el-n2) on the common_voice_11_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5083
-- Wer: 10.2712
+- Loss: 0.5645
+- Wer: 9.9276
 
 ## Model description
 
@@ -62,14 +59,21 @@ 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: 2000
+- training_steps: 9000
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Wer     |
 |:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.0014        | 58.82  | 1000 | 0.4944          | 10.3640 |
-| 0.0007        | 117.65 | 2000 | 0.5083          | 10.2712 |
+| 0.0014        | 58.82  | 1000 | 0.4951          | 10.3640 |
+| 0.0006        | 117.65 | 2000 | 0.5181          | 10.2805 |
+| 0.0007        | 175.82 | 3000 | 0.5317          | 10.1133 |
+| 0.0004        | 234.65 | 4000 | 0.5396          | 10.1226 |
+| 0.0004        | 293.47 | 5000 | 0.5532          | 10.1040 |
+| 0.0013        | 352.29 | 6000 | 0.5645          | 10.0854 |
+| 0.0002        | 411.12 | 7000 | 0.5669          | 10.1133 |
+| 0.0001        | 469.94 | 8000 | 0.5669          | 9.8997  |
+| 0.0001        | 528.76 | 9000 | 0.5645          | 9.9276  |
 
 
 ### Framework versions