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README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+base_model: ntu-spml/distilhubert
+model-index:
+- name: distilhubert-finetuned-gtzan
+  results:
+  - task:
+      type: audio-classification
+      name: Audio Classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      split: None
+    metrics:
+    - type: accuracy
+      value: 0.9319319319319319
+      name: Accuracy
+---
+
+<!-- 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-gtzan
+
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2387
+- Accuracy: 0.9319
+
+## 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: 0.001
+- train_batch_size: 6
+- eval_batch_size: 6
+- seed: 42
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.7644        | 1.0   | 167  | 1.7832          | 0.3554   |
+| 1.2856        | 2.0   | 334  | 1.4226          | 0.4745   |
+| 1.2123        | 3.0   | 501  | 1.0047          | 0.6737   |
+| 0.6613        | 4.0   | 668  | 0.8091          | 0.6987   |
+| 0.6442        | 5.0   | 835  | 0.6713          | 0.7858   |
+| 0.7172        | 6.0   | 1002 | 0.5749          | 0.8238   |
+| 0.5394        | 7.0   | 1169 | 0.5079          | 0.8408   |
+| 0.3853        | 8.0   | 1336 | 0.4574          | 0.8539   |
+| 0.5441        | 9.0   | 1503 | 0.3729          | 0.8869   |
+| 0.5062        | 10.0  | 1670 | 0.3319          | 0.9009   |
+| 0.3955        | 11.0  | 1837 | 0.3745          | 0.8849   |
+| 0.3112        | 12.0  | 2004 | 0.2752          | 0.9289   |
+| 0.2887        | 13.0  | 2171 | 0.2544          | 0.9289   |
+| 0.2038        | 14.0  | 2338 | 0.2344          | 0.9329   |
+| 0.2374        | 15.0  | 2505 | 0.2387          | 0.9319   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0
+## Training procedure
+
+
+### Framework versions
+
+
+- PEFT 0.6.2

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": {
+    "base_model_class": "HubertForSequenceClassification",
+    "parent_library": "transformers.models.hubert.modeling_hubert"
+  },
+  "base_model_name_or_path": "ntu-spml/distilhubert",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 1,
+  "lora_dropout": 0.0,
+  "modules_to_save": [
+    "classifier"
+  ],
+  "peft_type": "LORA",
+  "r": 1,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "output_dense",
+    "projector",
+    "out_proj",
+    "q_proj",
+    "intermediate_dense",
+    "k_proj",
+    "v_proj"
+  ],
+  "task_type": null
+}

adapter_model.safetensors

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+oid sha256:4972889e485c53e67906a9e6e3a78133c5bdf3324e5715ac7f9dd9407a9856ba
+size 128760