End of training

README.md

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+---
+base_model: wetdog/TUT-urban-acoustic-scenes-2018-development
+tags:
+- audio-classification
+- generated_from_trainer
+datasets:
+- acoustic-scenes
+metrics:
+- accuracy
+model-index:
+- name: ast-finetuned-audioset-10-10-0.4593-TUT-acoustic-scenes
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: TUT-urban-acoustic-scenes-2018-development
+      type: acoustic-scenes
+      args: 'split: train'
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9484375
+---
+
+<!-- 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-TUT-acoustic-scenes
+
+This model is a fine-tuned version of [wetdog/TUT-urban-acoustic-scenes-2018-development](https://huggingface.co/wetdog/TUT-urban-acoustic-scenes-2018-development) on the TUT-urban-acoustic-scenes-2018-development dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1450
+- Accuracy: 0.9484
+
+## 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: 3e-05
+- train_batch_size: 4
+- 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
+- training_steps: 500
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4236        | 1.0   | 500  | 0.1450          | 0.9484   |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3