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: default
+      split: train
+      args: default
+    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. -->
+
+# 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: 0.4268
+- 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 4
+- 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: 15
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 2.1998        | 0.8850  | 100  | 2.0267          | 0.34     |
+| 1.8078        | 1.7699  | 200  | 1.5776          | 0.51     |
+| 1.4427        | 2.6549  | 300  | 1.3546          | 0.57     |
+| 1.1903        | 3.5398  | 400  | 1.1145          | 0.63     |
+| 0.8872        | 4.4248  | 500  | 0.9314          | 0.74     |
+| 0.8191        | 5.3097  | 600  | 0.9010          | 0.73     |
+| 0.6717        | 6.1947  | 700  | 0.8036          | 0.75     |
+| 0.576         | 7.0796  | 800  | 0.9977          | 0.75     |
+| 0.481         | 7.9646  | 900  | 0.7552          | 0.81     |
+| 0.3211        | 8.8496  | 1000 | 0.6521          | 0.83     |
+| 0.2719        | 9.7345  | 1100 | 0.5343          | 0.86     |
+| 0.1922        | 10.6195 | 1200 | 0.6005          | 0.87     |
+| 0.1799        | 11.5044 | 1300 | 0.6158          | 0.84     |
+| 0.1159        | 12.3894 | 1400 | 0.5496          | 0.88     |
+| 0.0883        | 13.2743 | 1500 | 0.5128          | 0.88     |
+| 0.0536        | 14.1593 | 1600 | 0.4268          | 0.9      |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1

model.safetensors

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