Model save

README.md

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+---
+library_name: transformers
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bird-call-classification
+  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. -->
+
+# bird-call-classification
+
+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 an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0735
+- Accuracy: 0.9799
+- Precision: 0.9579
+- Recall: 1.0
+- F1: 0.9785
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- 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
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 50   | 0.2127          | 0.9497   | 0.9175    | 0.9780 | 0.9468 |
+| No log        | 2.0   | 100  | 0.1252          | 0.9698   | 0.9474    | 0.9890 | 0.9677 |
+| No log        | 3.0   | 150  | 0.1037          | 0.9749   | 0.9479    | 1.0    | 0.9733 |
+| No log        | 4.0   | 200  | 0.0947          | 0.9698   | 0.9381    | 1.0    | 0.9681 |
+| No log        | 5.0   | 250  | 0.0850          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
+| No log        | 6.0   | 300  | 0.0802          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
+| No log        | 7.0   | 350  | 0.0789          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
+| No log        | 8.0   | 400  | 0.0769          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
+| No log        | 9.0   | 450  | 0.0736          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
+| 0.1077        | 10.0  | 500  | 0.0735          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
+
+
+### Framework versions
+
+- Transformers 4.48.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

all_results.json

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+{
+    "epoch": 10.0,
+    "total_flos": 5.3955140555636736e+17,
+    "train_loss": 0.1076729736328125,
+    "train_runtime": 3647.2066,
+    "train_samples_per_second": 2.182,
+    "train_steps_per_second": 0.137
+}

train_results.json

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+{
+    "epoch": 10.0,
+    "total_flos": 5.3955140555636736e+17,
+    "train_loss": 0.1076729736328125,
+    "train_runtime": 3647.2066,
+    "train_samples_per_second": 2.182,
+    "train_steps_per_second": 0.137
+}