End of training

README.md

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+---
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9
+---
+
+<!-- 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-finetuned-gtzan
+
+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 GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4248
+- Accuracy: 0.9
+
+## 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: 4e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9212        | 1.0   | 112  | 0.6617          | 0.79     |
+| 0.4306        | 2.0   | 225  | 0.5650          | 0.81     |
+| 0.3493        | 3.0   | 337  | 0.3763          | 0.88     |
+| 0.0369        | 4.0   | 450  | 0.5402          | 0.83     |
+| 0.0018        | 5.0   | 562  | 0.4543          | 0.9      |
+| 0.0025        | 6.0   | 675  | 0.5821          | 0.85     |
+| 0.0009        | 7.0   | 787  | 0.4905          | 0.89     |
+| 0.0001        | 8.0   | 900  | 0.5396          | 0.86     |
+| 0.0871        | 9.0   | 1012 | 0.7212          | 0.86     |
+| 0.0001        | 10.0  | 1125 | 0.4179          | 0.9      |
+| 0.0001        | 11.0  | 1237 | 0.5138          | 0.9      |
+| 0.0001        | 12.0  | 1350 | 0.4133          | 0.9      |
+| 0.0001        | 13.0  | 1462 | 0.4273          | 0.9      |
+| 0.0001        | 14.0  | 1575 | 0.4278          | 0.9      |
+| 0.0001        | 14.93 | 1680 | 0.4248          | 0.9      |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.1

model.safetensors

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