End of training

README.md

@@ -8,9 +8,24 @@ tags:
 - generated_from_trainer
 datasets:
 - mozilla-foundation/common_voice_17_0
+metrics:
+- wer
 model-index:
 - name: whisper-large-marathi
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 17
+      type: mozilla-foundation/common_voice_17_0
+      config: mr
+      split: test
+      args: mr
+    metrics:
+    - name: Wer
+      type: wer
+      value: 11.99582494594796
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -19,6 +34,10 @@ should probably proofread and complete it, then remove this comment. -->
 # whisper-large-marathi
 
 This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1845
+- Wer Ortho: 32.4713
+- Wer: 11.9958
 
 ## Model description
 
@@ -46,16 +65,20 @@ 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: 20
-- training_steps: 200
+- training_steps: 500
 - mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
+| 0.1771        | 1.0   | 250  | 0.2041          | 36.0371   | 13.7851 |
+| 0.0806        | 2.0   | 500  | 0.1845          | 32.4713   | 11.9958 |
 
 
 ### Framework versions
 
 - Transformers 4.44.2
-- Pytorch 2.4.1+cu121
-- Datasets 3.0.0
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
 - Tokenizers 0.19.1