End of training

README.md

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+---
+base_model: facebook/wav2vec2
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: facebook/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: 0.4
+---
+
+<!-- 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. -->
+
+# facebook/wav2vec2-base-finetuned-gtzan
+
+This model is a fine-tuned version of [facebook/wav2vec2](https://huggingface.co/facebook/wav2vec2) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.0140
+- Accuracy: 0.4
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.96  | 6    | 2.2871          | 0.195    |
+| 2.2933        | 1.92  | 12   | 2.2658          | 0.18     |
+| 2.2933        | 2.88  | 18   | 2.2214          | 0.275    |
+| 2.2388        | 4.0   | 25   | 2.1885          | 0.29     |
+| 2.1455        | 4.96  | 31   | 2.1246          | 0.38     |
+| 2.1455        | 5.92  | 37   | 2.1139          | 0.35     |
+| 2.0823        | 6.88  | 43   | 2.0462          | 0.36     |
+| 2.0279        | 8.0   | 50   | 2.0282          | 0.405    |
+| 2.0279        | 8.96  | 56   | 2.0133          | 0.405    |
+| 1.9928        | 9.6   | 60   | 2.0140          | 0.4      |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

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