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
+- recall
+- precision
+- f1
+model-index:
+- name: AST_EmoRecog_Model_v4
+  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_EmoRecog_Model_v4
+
+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: 1.4615
+- Accuracy: 0.5159
+- Recall: 0.4007
+- Precision: 0.4956
+- F1: 0.4090
+
+## 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: 16
+- eval_batch_size: 16
+- 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: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 1.4443        | 1.0   | 377  | 1.3359          | 0.4695   | 0.3408 | 0.4793    | 0.3099 |
+| 1.1556        | 2.0   | 754  | 1.2506          | 0.5266   | 0.3877 | 0.6026    | 0.3970 |
+| 0.8988        | 3.0   | 1131 | 1.2633          | 0.5279   | 0.4175 | 0.5148    | 0.4208 |
+| 0.6187        | 4.0   | 1508 | 1.3426          | 0.5279   | 0.4031 | 0.5425    | 0.4153 |
+| 0.3944        | 5.0   | 1885 | 1.4266          | 0.5206   | 0.4021 | 0.5256    | 0.4152 |
+| 0.2555        | 6.0   | 2262 | 1.4615          | 0.5159   | 0.4007 | 0.4956    | 0.4090 |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

model.safetensors

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