update model card README.md

README.md

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+---
+license: bsd-3-clause
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2
+  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_ft_env_aug_0-2
+
+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: 0.6899
+- Accuracy: 0.9643
+- Precision: 0.9694
+- Recall: 0.9643
+- F1: 0.9631
+
+## 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: 2e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 2.0165        | 1.0   | 28   | 1.6252          | 0.4643   | 0.5373    | 0.4643 | 0.4711 |
+| 1.3702        | 2.0   | 56   | 1.0553          | 0.8571   | 0.8929    | 0.8571 | 0.8536 |
+| 0.8861        | 3.0   | 84   | 0.6899          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+| 0.5655        | 4.0   | 112  | 0.4766          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+| 0.4232        | 5.0   | 140  | 0.3403          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+| 0.3148        | 6.0   | 168  | 0.2679          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+| 0.2335        | 7.0   | 196  | 0.2239          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+| 0.176         | 8.0   | 224  | 0.1979          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+| 0.1624        | 9.0   | 252  | 0.1824          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+| 0.1466        | 10.0  | 280  | 0.1781          | 0.9643   | 0.9694    | 0.9643 | 0.9631 |
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 2.0.0
+- Datasets 2.10.1
+- Tokenizers 0.11.0