update model card README.md

README.md

@@ -1,41 +1,38 @@
 ---
-language:
-- eu
 license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_13_0
+- common_voice_13_0
 metrics:
 - wer
 model-index:
-- name: Whisper Small Basque
+- name: openai/whisper-medium
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: mozilla-foundation/common_voice_13_0 eu
-      type: mozilla-foundation/common_voice_13_0
+      name: common_voice_13_0
+      type: common_voice_13_0
       config: eu
       split: test
       args: eu
     metrics:
     - name: Wer
       type: wer
-      value: 13.996111628660538
+      value: 13.179958686054519
 ---
 
 <!-- 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 Basque
+# openai/whisper-medium
 
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 eu dataset.
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_13_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2256
-- Wer: 13.9961
+- Loss: 0.2201
+- Wer: 13.1800
 
 ## Model description
 
@@ -61,18 +58,20 @@ 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: 5000
+- training_steps: 7000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.4198        | 0.2   | 1000 | 0.4102          | 28.3487 |
-| 0.2547        | 0.4   | 2000 | 0.3142          | 21.6432 |
-| 0.2145        | 0.6   | 3000 | 0.2610          | 17.5159 |
-| 0.0828        | 1.14  | 4000 | 0.2388          | 15.3003 |
-| 0.0729        | 1.34  | 5000 | 0.2256          | 13.9961 |
+| 0.4203        | 0.14  | 1000 | 0.4128          | 28.2656 |
+| 0.2693        | 0.29  | 2000 | 0.3240          | 22.0523 |
+| 0.2228        | 0.43  | 3000 | 0.2737          | 18.1437 |
+| 0.1002        | 1.1   | 4000 | 0.2554          | 16.3534 |
+| 0.0863        | 1.24  | 5000 | 0.2351          | 14.7880 |
+| 0.0636        | 1.39  | 6000 | 0.2251          | 13.5971 |
+| 0.0271        | 2.06  | 7000 | 0.2201          | 13.1800 |
 
 
 ### Framework versions