End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/hubert-base-ls960
+tags:
+- generated_from_trainer
+datasets:
+- UrbanSounds/UrbanSoundsNew
+metrics:
+- accuracy
+model-index:
+- name: hubert-base-ls960-finetuned-urbansound
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: urbansound
+      type: UrbanSounds/UrbanSoundsNew
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6086956521739131
+---
+
+<!-- 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. -->
+
+# hubert-base-ls960-finetuned-urbansound
+
+This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the urbansound dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1907
+- Accuracy: 0.6087
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Use OptimizerNames.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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.133         | 1.0   | 50   | 2.1532          | 0.2609   |
+| 2.0878        | 2.0   | 100  | 2.0094          | 0.3478   |
+| 1.8873        | 3.0   | 150  | 1.8741          | 0.2609   |
+| 1.6437        | 4.0   | 200  | 1.5861          | 0.4783   |
+| 1.5457        | 5.0   | 250  | 1.4944          | 0.4783   |
+| 1.181         | 6.0   | 300  | 1.4003          | 0.5217   |
+| 1.2324        | 7.0   | 350  | 1.2538          | 0.5217   |
+| 0.9965        | 8.0   | 400  | 1.1745          | 0.5217   |
+| 1.26          | 9.0   | 450  | 1.1725          | 0.6087   |
+| 1.0922        | 10.0  | 500  | 1.1907          | 0.6087   |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0

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