End of training

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: revix-classifier_3.0
+  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. -->
+
+# revix-classifier_3.0
+
+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: 0.3655
+- Accuracy: 0.8625
+- Precision: 0.8571
+- Recall: 0.8780
+- F1: 0.8675
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.4043        | 1.0   | 120  | 0.4144          | 0.8042   | 0.7794    | 0.8618 | 0.8185 |
+| 0.3386        | 2.0   | 240  | 0.5331          | 0.7958   | 0.7403    | 0.9268 | 0.8231 |
+| 0.2155        | 3.0   | 360  | 0.3678          | 0.8542   | 0.8667    | 0.8455 | 0.8560 |
+| 0.0992        | 4.0   | 480  | 0.3655          | 0.8625   | 0.8571    | 0.8780 | 0.8675 |
+
+
+### Framework versions
+
+- Transformers 4.56.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.0