End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/hubert-base-ls960
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: hubert-base-ls960-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: 0.82
+---
+
+<!-- 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. -->
+
+# hubert-base-ls960-finetuned-gtzan
+
+This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6653
+- Accuracy: 0.82
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.931         | 0.9956 | 112  | 1.8442          | 0.38     |
+| 1.4533        | 2.0    | 225  | 1.4234          | 0.56     |
+| 1.5759        | 2.9956 | 337  | 1.3121          | 0.58     |
+| 0.9118        | 4.0    | 450  | 1.1423          | 0.68     |
+| 0.9785        | 4.9956 | 562  | 0.9830          | 0.71     |
+| 0.7014        | 6.0    | 675  | 0.8055          | 0.8      |
+| 0.5983        | 6.9956 | 787  | 0.7071          | 0.76     |
+| 0.3568        | 8.0    | 900  | 0.7417          | 0.77     |
+| 0.4118        | 8.9956 | 1012 | 0.5920          | 0.83     |
+| 0.4934        | 9.9556 | 1120 | 0.6653          | 0.82     |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.20.3

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