End of training

README.md

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+---
+library_name: transformers
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+datasets:
+- kim2024military
+metrics:
+- accuracy
+model-index:
+- name: ast-finetuned-audioset-10-10-0.4593-finetuned-MAD
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: MAD
+      type: kim2024military
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9344262295081968
+---
+
+<!-- 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. -->
+
+# ast-finetuned-audioset-10-10-0.4593-finetuned-MAD
+
+This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the MAD dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0444
+- Accuracy: 0.9344
+
+## 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: 16
+- eval_batch_size: 16
+- 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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2166        | 1.0   | 402  | 0.5008          | 0.8959   |
+| 0.4771        | 2.0   | 804  | 0.7085          | 0.9257   |
+| 0.1525        | 3.0   | 1206 | 0.9449          | 0.9373   |
+| 0.1688        | 4.0   | 1608 | 1.1073          | 0.9219   |
+| 0.1975        | 5.0   | 2010 | 1.2495          | 0.9209   |
+| 0.0           | 6.0   | 2412 | 1.0608          | 0.9306   |
+| 0.0           | 7.0   | 2814 | 1.0338          | 0.9344   |
+| 0.0           | 8.0   | 3216 | 1.0192          | 0.9373   |
+| 0.0           | 9.0   | 3618 | 1.0345          | 0.9344   |
+| 0.0           | 10.0  | 4020 | 1.0444          | 0.9344   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.4.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

model.safetensors

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