End of training

README.md

@@ -8,22 +8,9 @@ tags:
 - generated_from_trainer
 datasets:
 - stdbug/common-voice-17-ba
-metrics:
-- wer
 model-index:
 - name: Whisper base bashkir
-  results:
-  - task:
-      type: automatic-speech-recognition
-      name: Automatic Speech Recognition
-    dataset:
-      name: Common Voice 17.0 (ba)
-      type: stdbug/common-voice-17-ba
-      args: 'config: ba, split: test'
-    metrics:
-    - type: wer
-      value: 37.07627118644068
-      name: Wer
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +19,6 @@ 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: 0.2252
-- Wer: 37.0763
 
 ## Model description
 
@@ -54,22 +38,15 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 4
+- eval_batch_size: 4
 - 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: 173
-- training_steps: 1730
+- lr_scheduler_warmup_steps: 500
+- training_steps: 33418
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Wer     |
-|:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.2013        | 0.9994 | 1730 | 0.2252          | 37.0763 |
-
-
 ### Framework versions
 
 - Transformers 4.48.1

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "stdbug/whisper-base-ba",
+  "_name_or_path": "openai/whisper-base",
   "activation_dropout": 0.0,
   "activation_function": "gelu",
   "apply_spec_augment": false,

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