End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- gtzan
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-base-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: gtzan
+      type: gtzan
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.85
+---
+
+<!-- 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: 0.9600
+- Accuracy: 0.85
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.2696        | 0.99  | 28   | 2.1350          | 0.45     |
+| 1.9724        | 1.98  | 56   | 1.7939          | 0.63     |
+| 1.7172        | 2.97  | 84   | 1.6356          | 0.58     |
+| 1.5428        | 4.0   | 113  | 1.4019          | 0.71     |
+| 1.3184        | 4.99  | 141  | 1.3236          | 0.73     |
+| 1.2897        | 5.98  | 169  | 1.1980          | 0.79     |
+| 1.1657        | 6.97  | 197  | 1.0928          | 0.84     |
+| 1.0407        | 8.0   | 226  | 1.0616          | 0.83     |
+| 0.9717        | 8.99  | 254  | 0.9931          | 0.87     |
+| 0.9158        | 9.91  | 280  | 0.9600          | 0.85     |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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