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README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-base
+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: 0.9833774639599883
+---
+
+<!-- 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-base](https://huggingface.co/openai/whisper-base) on the superb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1152
+- Accuracy: 0.9834
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.6909 | 1.0 | 1597 | 0.1572 | 0.9651 |
+| 0.0891 | 2.0 | 3194 | 0.1597 | 0.9660 |
+| 0.0676 | 3.0 | 4791 | 0.1304 | 0.9719 |
+| 0.0475 | 4.0 | 6388 | 0.0999 | 0.9796 |
+| 0.0433 | 5.0 | 7985 | 0.1079 | 0.9798 |
+| 0.0284 | 6.0 | 9582 | 0.1089 | 0.9803 |
+| 0.0236 | 7.0 | 11179 | 0.1162 | 0.9819 |
+| 0.0193 | 8.0 | 12776 | 0.1152 | 0.9834 |
+| 0.0111 | 9.0 | 14373 | 0.1272 | 0.9821 |
+| 0.0088 | 10.0 | 15970 | 0.1306 | 0.9826 |
+
+
+### 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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+ "test_accuracy": 0.9438493995456021,
+ "test_loss": 0.3403080701828003,
+ "test_runtime": 25.5856,
+ "test_samples_per_second": 120.42,
+ "test_steps_per_second": 0.508,
+ "total_flos": 1.46834375382144e+19,
+ "train_accuracy": 0.9970055192390496,
+ "train_loss": 0.010813809931278229,
+ "train_runtime": 278.2509,
+ "train_samples_per_second": 183.626,
+ "train_steps_per_second": 45.908
+}

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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