End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: distil-whisper/distil-medium.en
+tags:
+- generated_from_trainer
+datasets:
+- speech_commands
+metrics:
+- accuracy
+model-index:
+- name: distil-medium.en-ft-kws-speech-commands
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: Speech Commands
+      type: speech_commands
+      config: v0.02
+      split: test
+      args: v0.02
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 1.0
+---
+
+<!-- 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. -->
+
+# distil-medium.en-ft-kws-speech-commands
+
+This model is a fine-tuned version of [distil-whisper/distil-medium.en](https://huggingface.co/distil-whisper/distil-medium.en) on the Speech Commands dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0
+- Accuracy: 1.0
+
+## 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: 64
+- eval_batch_size: 64
+- 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0           | 1.0   | 49   | 0.0000          | 1.0      |
+| 0.0           | 2.0   | 98   | 0.0             | 1.0      |
+| 0.0           | 3.0   | 147  | 0.0             | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.4.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3