End of training

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- generated_from_trainer
+datasets:
+- speech_commands
+metrics:
+- accuracy
+model-index:
+- name: whisper-base-speech-commands
+  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-speech-commands
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the speech_commands dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1307
+- 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2604        | 1.0   | 412  | 1.0617          | 0.7977   |
+| 0.1168        | 2.0   | 824  | 1.0024          | 0.8017   |
+| 0.1527        | 3.0   | 1236 | 0.9757          | 0.8022   |
+| 0.0637        | 4.0   | 1648 | 1.0066          | 0.8004   |
+| 0.0631        | 5.0   | 2060 | 1.0504          | 0.8053   |
+| 0.0554        | 6.0   | 2472 | 1.1307          | 0.8067   |
+| 0.1075        | 7.0   | 2884 | 1.1664          | 0.8017   |
+| 0.021         | 8.0   | 3296 | 1.4746          | 0.8044   |
+| 0.0144        | 9.0   | 3708 | 1.3729          | 0.8044   |
+| 0.0158        | 10.0  | 4120 | 1.3561          | 0.8040   |
+| 0.0504        | 11.0  | 4532 | 1.3289          | 0.8053   |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

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