End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base-960h
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-base-960h-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: 0.73
+---
+
+<!-- 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-960h-finetuned-gtzan
+
+This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0690
+- Accuracy: 0.73
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 2.3011        | 0.9956  | 56   | 2.2915          | 0.1      |
+| 2.2365        | 1.9911  | 112  | 2.1198          | 0.37     |
+| 1.9162        | 2.9867  | 168  | 1.9024          | 0.42     |
+| 1.7154        | 4.0     | 225  | 1.7397          | 0.39     |
+| 1.757         | 4.9956  | 281  | 1.5732          | 0.47     |
+| 1.546         | 5.9911  | 337  | 1.5172          | 0.47     |
+| 1.5738        | 6.9867  | 393  | 1.3950          | 0.54     |
+| 1.2893        | 8.0     | 450  | 1.4202          | 0.56     |
+| 1.2745        | 8.9956  | 506  | 1.2819          | 0.59     |
+| 1.2632        | 9.9911  | 562  | 1.2788          | 0.66     |
+| 1.2195        | 10.9867 | 618  | 1.1909          | 0.63     |
+| 1.1151        | 12.0    | 675  | 1.1605          | 0.62     |
+| 1.0165        | 12.9956 | 731  | 1.1202          | 0.67     |
+| 0.9418        | 13.9911 | 787  | 1.0747          | 0.73     |
+| 0.9686        | 14.9333 | 840  | 1.0690          | 0.73     |
+
+
+### Framework versions
+
+- Transformers 4.43.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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