End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: yojul/wav2vec2-base-one-shot-hip-hop-drums-clf
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-base-one-shot-hip-hop-drums-clf-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: 0.74
+---
+
+<!-- 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-one-shot-hip-hop-drums-clf-finetuned-gtzan
+
+This model is a fine-tuned version of [yojul/wav2vec2-base-one-shot-hip-hop-drums-clf](https://huggingface.co/yojul/wav2vec2-base-one-shot-hip-hop-drums-clf) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9288
+- Accuracy: 0.74
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.7695        | 1.0   | 100  | 1.9632          | 0.345    |
+| 1.3851        | 2.0   | 200  | 1.3526          | 0.56     |
+| 1.0214        | 3.0   | 300  | 1.3209          | 0.58     |
+| 0.725         | 4.0   | 400  | 1.0294          | 0.72     |
+| 0.6425        | 5.0   | 500  | 0.9288          | 0.74     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1