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README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- audio-classification
+- generated_from_trainer
+datasets:
+- superb
+metrics:
+- accuracy
+model-index:
+- name: superb_ks_42
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: superb
+      type: superb
+      config: ks
+      split: validation
+      args: ks
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9801412180052956
+---
+
+<!-- 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. -->
+
+# superb_ks_42
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the superb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1434
+- Accuracy: 0.9801
+
+## 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: 32
+- eval_batch_size: 4
+- 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.8486        | 1.0   | 1597  | 0.2380          | 0.9385   |
+| 0.0986        | 2.0   | 3194  | 0.1777          | 0.9598   |
+| 0.0773        | 3.0   | 4791  | 0.1249          | 0.9738   |
+| 0.0532        | 4.0   | 6388  | 0.1078          | 0.9782   |
+| 0.0472        | 5.0   | 7985  | 0.1258          | 0.9766   |
+| 0.0322        | 6.0   | 9582  | 0.1365          | 0.9772   |
+| 0.0258        | 7.0   | 11179 | 0.1338          | 0.9798   |
+| 0.0231        | 8.0   | 12776 | 0.1447          | 0.9796   |
+| 0.0171        | 9.0   | 14373 | 0.1435          | 0.9797   |
+| 0.0142        | 10.0  | 15970 | 0.1434          | 0.9801   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

all_results.json

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+    "eval_steps_per_second": 1.059,
+    "test_accuracy": 0.9425511197663097,
+    "test_loss": 0.35165315866470337,
+    "test_runtime": 16.1313,
+    "test_samples_per_second": 190.995,
+    "test_steps_per_second": 0.806,
+    "total_flos": 5.6903389435008e+18,
+    "train_accuracy": 0.9971816651661644,
+    "train_loss": 0.009092943742871284,
+    "train_runtime": 118.8228,
+    "train_samples_per_second": 430.002,
+    "train_steps_per_second": 107.505
+}

config.json

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eval_results.json

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preprocessor_config.json

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test_results.json

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train_results.json

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