End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-base-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: 0.88
+---
+
+<!-- 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. -->
+
+# wav2vec2-base-finetuned-gtzan
+
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6411
+- Accuracy: 0.88
+
+## 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: 6e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 13
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.8965        | 1.0   | 113  | 1.8976          | 0.28     |
+| 1.3295        | 2.0   | 226  | 1.4744          | 0.52     |
+| 1.159         | 3.0   | 339  | 1.0918          | 0.66     |
+| 0.5861        | 4.0   | 452  | 0.9779          | 0.74     |
+| 1.0464        | 5.0   | 565  | 0.9167          | 0.73     |
+| 0.8294        | 6.0   | 678  | 0.8404          | 0.75     |
+| 0.462         | 7.0   | 791  | 0.8323          | 0.78     |
+| 0.1366        | 8.0   | 904  | 0.7485          | 0.8      |
+| 0.179         | 9.0   | 1017 | 0.6523          | 0.87     |
+| 0.0361        | 10.0  | 1130 | 0.6313          | 0.87     |
+| 0.2355        | 11.0  | 1243 | 0.6609          | 0.88     |
+| 0.0543        | 12.0  | 1356 | 0.6559          | 0.88     |
+| 0.0201        | 13.0  | 1469 | 0.6411          | 0.88     |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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