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: 0.7307692307692307
+---
+
+<!-- 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: 1.2479
+- Accuracy: 0.7308
+
+## 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: 10
+- eval_batch_size: 10
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 18
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9797        | 1.0   | 70   | 1.9644          | 0.3718   |
+| 1.4254        | 2.0   | 140  | 1.7058          | 0.4359   |
+| 1.3827        | 3.0   | 210  | 1.3349          | 0.5769   |
+| 1.1156        | 4.0   | 280  | 1.2080          | 0.6795   |
+| 0.7843        | 5.0   | 350  | 1.1072          | 0.6667   |
+| 0.7063        | 6.0   | 420  | 1.2091          | 0.6667   |
+| 0.4972        | 7.0   | 490  | 1.0370          | 0.7179   |
+| 0.6555        | 8.0   | 560  | 1.1193          | 0.6795   |
+| 0.4934        | 9.0   | 630  | 0.9080          | 0.7692   |
+| 0.1664        | 10.0  | 700  | 1.2513          | 0.6795   |
+| 0.3892        | 11.0  | 770  | 1.3065          | 0.6667   |
+| 0.0895        | 12.0  | 840  | 1.2479          | 0.7308   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

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