End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- calixtemayoraz/FMA-music-dataset
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-finetuned-FMA-music
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: FMA-music-dataset
+      type: calixtemayoraz/FMA-music-dataset
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.45754716981132076
+---
+
+<!-- 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. -->
+
+# distilhubert-finetuned-FMA-music
+
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the FMA-music-dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8929
+- Accuracy: 0.4575
+
+## 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: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.0384        | 1.0   | 238  | 2.2583          | 0.2358   |
+| 1.9204        | 2.0   | 476  | 2.1387          | 0.2972   |
+| 1.6768        | 3.0   | 714  | 1.9356          | 0.3774   |
+| 1.7940        | 4.0   | 952  | 1.8584          | 0.3868   |
+| 1.5281        | 5.0   | 1190 | 1.7814          | 0.4434   |
+| 1.1608        | 6.0   | 1428 | 1.8745          | 0.4151   |
+| 1.2103        | 7.0   | 1666 | 1.8066          | 0.4434   |
+| 0.8522        | 8.0   | 1904 | 1.8688          | 0.4434   |
+| 0.7455        | 9.0   | 2142 | 1.8818          | 0.4528   |
+| 0.5444        | 10.0  | 2380 | 1.8929          | 0.4575   |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0,
+  "return_attention_mask": true,
+  "sampling_rate": 16000
+}