End of training

README.md

@@ -8,9 +8,22 @@ tags:
 - generated_from_trainer
 datasets:
 - stdbug/common-voice-17-ba
+metrics:
+- wer
 model-index:
 - name: Whisper base bashkir
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 17.0 (ba)
+      type: stdbug/common-voice-17-ba
+      args: 'config: ba, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 35.15895985683671
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -19,6 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
 # Whisper base bashkir
 
 This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 17.0 (ba) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2265
+- Wer: 35.1590
 
 ## Model description
 
@@ -38,15 +54,22 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 33418
+- training_steps: 16709
 - mixed_precision_training: Native AMP
 
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|
+| 0.1674        | 0.9999 | 16709 | 0.2265          | 35.1590 |
+
+
 ### Framework versions
 
 - Transformers 4.48.1