End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-base.en
+tags:
+- generated_from_trainer
+datasets:
+- speech_commands
+metrics:
+- accuracy
+model-index:
+- name: whisper-base.en-speech-commands-v1
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: speech_commands
+      type: speech_commands
+      config: v0.02
+      split: None
+      args: v0.02
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8066546762589928
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# whisper-base.en-speech-commands-v1
+
+This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the speech_commands dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1638
+- Accuracy: 0.8067
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 96
+- eval_batch_size: 96
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 384
+- 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3306        | 1.0   | 103  | 1.1388          | 0.8022   |
+| 0.1314        | 2.0   | 206  | 1.1511          | 0.8022   |
+| 0.0672        | 3.0   | 309  | 1.1448          | 0.8062   |
+| 0.048         | 4.0   | 412  | 1.1638          | 0.8067   |
+| 0.034         | 5.0   | 515  | 1.1655          | 0.8058   |
+
+
+### Framework versions
+
+- Transformers 4.51.2
+- Pytorch 2.6.0+cu126
+- Datasets 3.5.0
+- Tokenizers 0.21.1

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