ast trainer push best model after 5 epochs fp16

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
+- recall
+- precision
+- f1
+model-index:
+- name: DL_Audio_Hatespeech_ast_trainer_push
+  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. -->
+
+# DL_Audio_Hatespeech_ast_trainer_push
+
+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: 0.6336
+- Accuracy: 0.6431
+- Recall: 0.7452
+- Precision: 0.6237
+- F1: 0.6790
+
+## 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: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Recall | Precision | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6432        | 0.9987 | 387  | 0.6686          | 0.5992   | 0.6580 | 0.5944    | 0.6245 |
+| 0.6414        | 2.0    | 775  | 0.6336          | 0.6431   | 0.7452 | 0.6237    | 0.6790 |
+| 0.6079        | 2.9987 | 1162 | 0.6505          | 0.6328   | 0.5783 | 0.6561    | 0.6148 |
+| 0.5088        | 4.0    | 1550 | 0.7122          | 0.6176   | 0.6624 | 0.6136    | 0.6371 |
+| 0.3005        | 4.9935 | 1935 | 0.9250          | 0.6099   | 0.6038 | 0.6176    | 0.6106 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.3.2
+- Tokenizers 0.19.1

model.safetensors

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