update model card README.md

README.md

@@ -1,40 +1,38 @@
 ---
-language:
-- eu
 license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_13_0
+- common_voice_16_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_16_0
+      type: common_voice_16_0
       config: eu
       split: test
       args: eu
     metrics:
     - name: Wer
       type: wer
-      value: 12.839726193851513
+      value: 9.188591686749389
 ---
 
-# Whisper Small Basque
+<!-- 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. -->
 
-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.
-It achieves the following results on the evaluation set:
-- Loss: 0.2287
-- Wer: 12.8397
+# openai/whisper-medium
 
-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)
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1503
+- Wer: 9.1886
 
 ## Model description
 
@@ -67,22 +65,22 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.4415        | 0.06  | 500  | 0.5092          | 36.9699 |
-| 0.4206        | 0.12  | 1000 | 0.4144          | 28.3365 |
-| 0.272         | 0.19  | 1500 | 0.3554          | 24.7438 |
-| 0.2681        | 0.25  | 2000 | 0.3271          | 22.1414 |
-| 0.2099        | 0.31  | 2500 | 0.2973          | 19.5350 |
-| 0.2283        | 0.38  | 3000 | 0.2760          | 18.5042 |
-| 0.1477        | 1.03  | 3500 | 0.2637          | 17.1493 |
-| 0.1008        | 1.09  | 4000 | 0.2592          | 16.3939 |
-| 0.0866        | 1.15  | 4500 | 0.2561          | 15.8066 |
-| 0.0915        | 1.21  | 5000 | 0.2411          | 15.0310 |
-| 0.0803        | 1.28  | 5500 | 0.2330          | 14.7616 |
-| 0.0674        | 1.34  | 6000 | 0.2325          | 13.8462 |
-| 0.0679        | 1.4   | 6500 | 0.2299          | 13.5809 |
-| 0.027         | 2.05  | 7000 | 0.2304          | 13.3805 |
-| 0.0231        | 2.11  | 7500 | 0.2287          | 12.8397 |
-| 0.0285        | 2.18  | 8000 | 0.2304          | 12.8883 |
+| 0.4647        | 0.06  | 500  | 0.4529          | 34.2140 |
+| 0.3163        | 0.12  | 1000 | 0.3516          | 26.0232 |
+| 0.3232        | 0.19  | 1500 | 0.2996          | 21.1825 |
+| 0.266         | 0.25  | 2000 | 0.2686          | 18.5126 |
+| 0.2383        | 0.31  | 2500 | 0.2489          | 16.9412 |
+| 0.1916        | 0.38  | 3000 | 0.2233          | 15.2831 |
+| 0.2009        | 0.44  | 3500 | 0.2134          | 14.1419 |
+| 0.2014        | 0.5   | 4000 | 0.2015          | 13.6579 |
+| 0.1964        | 0.56  | 4500 | 0.1853          | 12.0198 |
+| 0.1758        | 0.62  | 5000 | 0.1796          | 11.4651 |
+| 0.2067        | 0.69  | 5500 | 0.1679          | 10.7989 |
+| 0.213         | 0.75  | 6000 | 0.1618          | 10.3139 |
+| 0.1272        | 1.03  | 6500 | 0.1551          | 9.8687  |
+| 0.0744        | 1.09  | 7000 | 0.1534          | 9.5172  |
+| 0.0726        | 1.16  | 7500 | 0.1518          | 9.3240  |
+| 0.0627        | 1.22  | 8000 | 0.1503          | 9.1886  |
 
 
 ### Framework versions