End of training

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- gtzan
+metrics:
+- accuracy
+model-index:
+- name: whisper-small-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: gtzan
+      type: gtzan
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.91
+---
+
+<!-- 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-small-finetuned-gtzan
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the gtzan dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4896
+- Accuracy: 0.91
+
+## 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: 3e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.292         | 1.0   | 100  | 1.3642          | 0.595    |
+| 1.0263        | 2.0   | 200  | 0.9241          | 0.725    |
+| 0.5906        | 3.0   | 300  | 0.9602          | 0.68     |
+| 0.2665        | 4.0   | 400  | 0.8529          | 0.745    |
+| 0.2222        | 5.0   | 500  | 0.6671          | 0.835    |
+| 0.1649        | 6.0   | 600  | 0.4792          | 0.9      |
+| 0.0018        | 7.0   | 700  | 0.7901          | 0.87     |
+| 0.0303        | 8.0   | 800  | 0.4475          | 0.925    |
+| 0.0011        | 9.0   | 900  | 0.5972          | 0.895    |
+| 0.0008        | 10.0  | 1000 | 0.5501          | 0.9      |
+| 0.0007        | 11.0  | 1100 | 0.5916          | 0.895    |
+| 0.0007        | 12.0  | 1200 | 0.5719          | 0.9      |
+| 0.0007        | 13.0  | 1300 | 0.5082          | 0.92     |
+| 0.0007        | 14.0  | 1400 | 0.4954          | 0.905    |
+| 0.0006        | 15.0  | 1500 | 0.4896          | 0.91     |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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