End of training

README.md

@@ -8,22 +8,9 @@ tags:
 - generated_from_trainer
 datasets:
 - mozilla-foundation/common_voice_11_0
-metrics:
-- wer
 model-index:
 - name: Whisper Small Hi - Sanchit Gandhi
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 11.0
-      type: mozilla-foundation/common_voice_11_0
-      args: 'config: hi, split: test'
-    metrics:
-    - name: Wer
-      type: wer
-      value: 100.0
+  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 Small Hi - Sanchit Gandhi
 
 This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.2453
-- Wer: 100.0
 
 ## Model description
 
@@ -54,8 +38,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 16
-- eval_batch_size: 8
+- train_batch_size: 32
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
@@ -63,19 +47,9 @@ The following hyperparameters were used during training:
 - training_steps: 4000
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Wer   |
-|:-------------:|:------:|:----:|:---------------:|:-----:|
-| 0.0           | 1000.0 | 1000 | 0.7004          | 100.0 |
-| 0.0           | 2000.0 | 2000 | 0.9834          | 100.0 |
-| 0.0           | 3000.0 | 3000 | 1.1407          | 100.0 |
-| 0.0           | 4000.0 | 4000 | 1.2453          | 100.0 |
-
-
 ### Framework versions
 
 - Transformers 4.46.3
-- Pytorch 2.5.1+cu121
+- Pytorch 2.4.0
 - Datasets 3.1.0
-- Tokenizers 0.20.3
+- Tokenizers 0.20.0

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