End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/hubert-large-ls960-ft
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: hubert-large-ls960-ft-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: 0.75
+---
+
+<!-- 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-large-ls960-ft-finetuned-gtzan
+
+This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8290
+- Accuracy: 0.75
+
+## 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: 5
+- eval_batch_size: 5
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.1489        | 1.0   | 90   | 2.1400          | 0.24     |
+| 1.6277        | 2.0   | 180  | 1.6670          | 0.46     |
+| 1.5479        | 3.0   | 270  | 1.4687          | 0.47     |
+| 1.1795        | 4.0   | 360  | 1.3815          | 0.56     |
+| 1.1491        | 5.0   | 450  | 1.0969          | 0.63     |
+| 0.8421        | 6.0   | 540  | 1.0707          | 0.65     |
+| 1.1917        | 7.0   | 630  | 0.8761          | 0.71     |
+| 0.7243        | 8.0   | 720  | 0.8741          | 0.72     |
+| 0.6959        | 9.0   | 810  | 0.8417          | 0.76     |
+| 0.6921        | 10.0  | 900  | 0.8290          | 0.75     |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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