Update README.md

README.md

@@ -5,6 +5,7 @@ license: apache-2.0
 tags:
 - whisper-event
 - finnish
+- speech-recognition
 datasets:
 - mozilla-foundation/common_voice_11_0
 - google/fleurs
@@ -46,18 +47,19 @@ model-index:
     - name: Cer
       type: cer
       value: 3.23
+library_name: transformers
+pipeline_tag: automatic-speech-recognition
 ---
 
-<h3>This is our improved Whisper model that is now finetuned from OpenAI Whisper Large V3 </h3>
-<p>We improve from our previously finetuned V2 model <a>https://huggingface.co/Finnish-NLP/whisper-large-v2-finnish</a> </p>
-<p>CV11 WER 10.42 --> 8.23</p>
-<p>Fleurs WER 10.20 --> 8.21</p>
-<p>Model was trained on RTX4080 for 32k steps with batch size 8, gradient accumulation 2</p>
-
+<h3>This is our improved Whisper v3 model that is now finetuned from OpenAI Whisper Large V3 </h3>
+<p>We improve from our previously finetuned Whisper V2 model in the following manner<a>https://huggingface.co/Finnish-NLP/whisper-large-v2-finnish</a> </p>
+<p>CV11 (Common Voice 11 test set) WER (Word error rate) 10.42 --> 8.23</p>
+<p>Fleurs (A speech recognition test set by Google) WER (Word error rate) 10.20 --> 8.21</p>
+<p>Model was trained on Nvidia RTX4080 for 32k steps with batch size 8, gradient accumulation 2</p>
 
 <br></br>
 
-Original Whisper Large V3
+Original OpenAI Whisper Large V3
 - CV11
   - WER: 14.81
   - WER NORMALIZED: 10.82
@@ -71,9 +73,9 @@ Original Whisper Large V3
   - CER NORMALIZED: 3.64
 
 
-After Finetuning V3:
+After Finetuning with Finnish data our V3 got these scores on the test set:
 
-  - @14000 steps
+  - @14000 finetuning steps
     - CV11
       - WER: 11.36
       - WER NORMALIZED: 8.31
@@ -86,7 +88,7 @@ After Finetuning V3:
       - CER: 2.26
       - CER NORMALIZED: 3.54
 
-  - @32000 steps
+  - @32000 finetuning steps
     - CV11
       - WER: 11.47
       - WER NORMALIZED: 8.23