End of training

README.md

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+---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-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: 0.85
+---
+
+<!-- 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. -->
+
+# 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: 0.5960
+- 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: 5e-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: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.2592        | 0.99  | 28   | 2.2167          | 0.25     |
+| 1.8769        | 1.98  | 56   | 1.8139          | 0.49     |
+| 1.5783        | 2.97  | 84   | 1.5107          | 0.61     |
+| 1.3068        | 4.0   | 113  | 1.2779          | 0.68     |
+| 1.1062        | 4.99  | 141  | 1.0318          | 0.8      |
+| 1.0125        | 5.98  | 169  | 0.9156          | 0.83     |
+| 0.8787        | 6.97  | 197  | 0.8099          | 0.86     |
+| 0.7658        | 8.0   | 226  | 0.7804          | 0.85     |
+| 0.7811        | 8.99  | 254  | 0.7448          | 0.83     |
+| 0.6369        | 9.98  | 282  | 0.6841          | 0.84     |
+| 0.4859        | 10.97 | 310  | 0.6353          | 0.85     |
+| 0.4705        | 12.0  | 339  | 0.6193          | 0.87     |
+| 0.4571        | 12.99 | 367  | 0.6090          | 0.86     |
+| 0.3999        | 13.98 | 395  | 0.5912          | 0.86     |
+| 0.4007        | 14.87 | 420  | 0.5960          | 0.85     |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.0
+- Tokenizers 0.15.0

runs/Dec29_10-03-10_a56ec407a47d/events.out.tfevents.1703844197.a56ec407a47d.2646.0

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