End of training

README.md

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+---
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gunshot
+  results: []
+---
+
+<!-- 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-gunshot
+
+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 None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8955
+- Accuracy: 0.7647
+
+## 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: 2
+- eval_batch_size: 2
+- 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.771         | 1.0   | 341  | 1.4439          | 0.6294   |
+| 3.4687        | 2.0   | 682  | 1.2804          | 0.6824   |
+| 0.7887        | 3.0   | 1023 | 0.5085          | 0.7412   |
+| 0.4093        | 4.0   | 1364 | 0.4299          | 0.7882   |
+| 0.1765        | 5.0   | 1705 | 0.3885          | 0.8471   |
+| 0.1055        | 6.0   | 2046 | 0.4319          | 0.7941   |
+| 0.1341        | 7.0   | 2387 | 0.4773          | 0.8      |
+| 0.0722        | 8.0   | 2728 | 0.8647          | 0.7412   |
+| 0.156         | 9.0   | 3069 | 0.9191          | 0.7647   |
+| 0.0377        | 10.0  | 3410 | 0.8955          | 0.7647   |
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.0.0
+- Datasets 2.15.1.dev0
+- Tokenizers 0.15.0

model.safetensors

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