End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- kim2024military
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-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: 0.8900675024108003
+---
+
+<!-- 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. -->
+
+# distilhubert-finetuned-MAD
+
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the MAD dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6123
+- Accuracy: 0.8901
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.624         | 1.0   | 402  | 0.6450          | 0.8245   |
+| 0.425         | 2.0   | 804  | 0.4776          | 0.8708   |
+| 0.0852        | 3.0   | 1206 | 0.5281          | 0.8698   |
+| 0.2255        | 4.0   | 1608 | 0.7678          | 0.8650   |
+| 0.0522        | 5.0   | 2010 | 1.0425          | 0.8814   |
+| 0.2029        | 6.0   | 2412 | 1.3518          | 0.8930   |
+| 0.0206        | 7.0   | 2814 | 1.5771          | 0.8939   |
+| 0.0           | 8.0   | 3216 | 1.5804          | 0.8872   |
+| 0.2069        | 9.0   | 3618 | 1.6365          | 0.8891   |
+| 0.1882        | 10.0  | 4020 | 1.6123          | 0.8901   |
+
+
+### 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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