update model card README.md

README.md

@@ -1,41 +1,38 @@
 ---
-language:
-- sv
 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 Large Swedish
+- name: openai/whisper-large-v2
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: mozilla-foundation/common_voice_11_0 sv-SE
-      type: mozilla-foundation/common_voice_11_0
+      name: common_voice_11_0
+      type: common_voice_11_0
       config: sv-SE
       split: test
       args: sv-SE
     metrics:
     - name: Wer
       type: wer
-      value: 27.269551195915078
+      value: 9.220639613007256
 ---
 
 <!-- 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 Large Swedish
+# openai/whisper-large-v2
 
-This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 sv-SE dataset.
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0057
-- Wer: 27.2696
+- Loss: 0.2337
+- Wer: 9.2206
 
 ## Model description
 
@@ -63,15 +60,18 @@ 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: 20
+- training_steps: 5000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer     |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|
-| No log        | 0.5   | 10   | 1.0278          | 36.6568 |
-| No log        | 1.0   | 20   | 1.0057          | 27.2696 |
+| 0.0695        | 0.2   | 1000 | 0.2695          | 12.4671 |
+| 0.0524        | 0.4   | 2000 | 0.2659          | 11.6367 |
+| 0.046         | 0.6   | 3000 | 0.2402          | 10.6557 |
+| 0.0342        | 0.8   | 4000 | 0.2339          | 10.1774 |
+| 0.0224        | 1.14  | 5000 | 0.2337          | 9.2206  |
 
 
 ### Framework versions