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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: 13.179958686054519
+      value: 14.119648426424725
 ---
 
 <!-- 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: 0.2201
-- Wer: 13.1800
+- Loss: 0.2376
+- Wer: 14.1196
 
 ## Model description
 
@@ -43,7 +40,7 @@ More information needed
 
 ## Intended uses & limitations
 
-If you need to use this model with [whisper.cpp](https://github.com/ggerganov/whisper.cpp), you can download the ggml file: [ggml-medium-eu.bin](https://huggingface.co/xezpeleta/whisper-medium-eu/blob/main/ggml-medium.eu.bin)
+More information needed
 
 ## Training and evaluation data
 
@@ -54,27 +51,36 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 6e-06
 - train_batch_size: 4
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 7000
+- training_steps: 8000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 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 |
+| 0.443         | 0.06  | 500  | 0.5037          | 37.4296 |
+| 0.4196        | 0.12  | 1000 | 0.4010          | 28.9137 |
+| 0.2823        | 0.19  | 1500 | 0.3453          | 24.6851 |
+| 0.2551        | 0.25  | 2000 | 0.3164          | 22.5789 |
+| 0.206         | 0.31  | 2500 | 0.2902          | 19.7922 |
+| 0.2327        | 0.38  | 3000 | 0.2707          | 18.9356 |
+| 0.1416        | 1.03  | 3500 | 0.2566          | 17.6921 |
+| 0.0998        | 1.09  | 4000 | 0.2551          | 16.8213 |
+| 0.095         | 1.15  | 4500 | 0.2511          | 16.3899 |
+| 0.0971        | 1.21  | 5000 | 0.2415          | 15.5393 |
+| 0.0964        | 1.28  | 5500 | 0.2336          | 15.1707 |
+| 0.072         | 1.34  | 6000 | 0.2353          | 14.7596 |
+| 0.0658        | 1.4   | 6500 | 0.2340          | 14.6766 |
+| 0.033         | 2.05  | 7000 | 0.2349          | 14.3768 |
+| 0.0288        | 2.11  | 7500 | 0.2371          | 14.1865 |
+| 0.0352        | 2.18  | 8000 | 0.2376          | 14.1196 |
 
 
 ### Framework versions