End of training

README.md

@@ -1,14 +1,33 @@
 ---
 library_name: peft
+language:
+- tr
 license: mit
 base_model: openai/whisper-large-v3-turbo
 tags:
+- asr
+- whisper
+- lora
+- Turkish
+- tr
 - generated_from_trainer
+datasets:
+- dcl-ai-team/CommonVoice-17_tr_bandpass_filter_telephonic
 metrics:
 - wer
 model-index:
 - name: v3-turbo-cv17-telephonic-lora
-  results: []
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: CommonVoice-17_tr_bandpass_filter_telephonic
+      type: dcl-ai-team/CommonVoice-17_tr_bandpass_filter_telephonic
+    metrics:
+    - type: wer
+      value: 14.208987174831321
+      name: Wer
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,7 +35,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # v3-turbo-cv17-telephonic-lora
 
-This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset.
+This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the CommonVoice-17_tr_bandpass_filter_telephonic dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.1411
 - Wer: 14.2090

lora_config.json

@@ -0,0 +1,15 @@
+{
+    "r": 32,
+    "lora_alpha": 8,
+    "target_modules": [
+        "fc2",
+        "out_proj",
+        "fc1",
+        "q_proj",
+        "k_proj",
+        "v_proj"
+    ],
+    "lora_dropout": 0.05,
+    "bias": "none",
+    "use_rslora": true
+}