Update README.md

README.md

@@ -1,3 +1,81 @@
----
-license: unknown
----
+---
+license: unknown
+datasets:
+- PolyAI/minds14
+language:
+- en
+metrics:
+- accuracy
+- wer
+- f1
+- bleu
+base_model:
+- openai/whisper-tiny
+pipeline_tag: automatic-speech-recognition
+
+model-index:
+- name: whisper-mind14-enUS
+  results:
+  - task:
+      type: ASR
+    dataset:
+      name: minds-14
+      type: enUS
+    metrics:
+    - name: Accuracy
+      type: Accuracy
+      value: 62.25
+  - task:
+      type: ASR
+    dataset:
+      name: minds-14
+      type: enUS
+    metrics:
+    - name: wer
+      type: wer
+      value: 0.38%
+  - task:
+      type: ASR
+    dataset:
+      name: minds-14
+      type: enUS
+    metrics:
+    - name: f1
+      type: f1
+      value: 0.6722
+  - task:
+      type: ASR
+    dataset:
+      name: minds-14
+      type: enUS
+    metrics:
+    - name: bleu
+      type: bleu
+      value: 0.0235
+---
+
+this model based on whisper-tiny model that trained with minds-14 dataset, only trained in english version : enUS
+
+example of using model to classify intent:
+
+```python
+>>> from transformers import pipeline
+
+model_id = "kairaamilanii/whisper-mind14-enUS"
+
+transcriber = pipeline(
+    "automatic-speech-recognition",
+    model=model_id,
+    chunk_length_s=30,
+    device="cuda:0" if torch.cuda.is_available() else "cpu",
+)
+
+audio_file = "/content/602b9a90963e11ccd901cbd0.wav"  # Replace with your audio file path
+
+text = transcriber(audio_file)
+text
+```
+example output:
+```python
+{'text': "hello i was looking at my recent transactions and i saw that there's a payment that i didn't make will you be able to stop this thank you"}
+```