End of training

README.md

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+---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-finetuned-gtzan-v2
+  results: []
+---
+
+<!-- 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-v2
+
+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: 0.5528
+- Accuracy: 0.86
+
+## 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: 16
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.2975        | 1.0   | 14   | 2.2790          | 0.26     |
+| 2.255         | 1.99  | 28   | 2.1863          | 0.39     |
+| 2.0948        | 2.99  | 42   | 1.9637          | 0.43     |
+| 1.847         | 3.98  | 56   | 1.7093          | 0.54     |
+| 1.5798        | 4.98  | 70   | 1.5095          | 0.62     |
+| 1.4674        | 5.97  | 84   | 1.3173          | 0.67     |
+| 1.2969        | 6.97  | 98   | 1.1894          | 0.72     |
+| 1.1472        | 7.96  | 112  | 1.0415          | 0.77     |
+| 0.9815        | 8.96  | 126  | 1.0004          | 0.74     |
+| 0.8838        | 9.96  | 140  | 0.8808          | 0.78     |
+| 0.8294        | 10.95 | 154  | 0.8551          | 0.78     |
+| 0.768         | 11.95 | 168  | 0.7939          | 0.79     |
+| 0.6499        | 12.94 | 182  | 0.7467          | 0.81     |
+| 0.6014        | 13.94 | 196  | 0.6995          | 0.82     |
+| 0.5296        | 14.93 | 210  | 0.7152          | 0.79     |
+| 0.4478        | 16.0  | 225  | 0.6561          | 0.83     |
+| 0.4082        | 17.0  | 239  | 0.6399          | 0.84     |
+| 0.374         | 17.99 | 253  | 0.6217          | 0.86     |
+| 0.3282        | 18.99 | 267  | 0.5991          | 0.85     |
+| 0.28          | 19.98 | 281  | 0.6043          | 0.84     |
+| 0.2754        | 20.98 | 295  | 0.5831          | 0.87     |
+| 0.2409        | 21.97 | 309  | 0.5680          | 0.85     |
+| 0.2172        | 22.97 | 323  | 0.5729          | 0.85     |
+| 0.1855        | 23.96 | 337  | 0.5645          | 0.86     |
+| 0.1729        | 24.96 | 351  | 0.5576          | 0.86     |
+| 0.161         | 25.96 | 365  | 0.5378          | 0.86     |
+| 0.1586        | 26.95 | 379  | 0.5662          | 0.86     |
+| 0.1452        | 27.95 | 393  | 0.5575          | 0.87     |
+| 0.1444        | 28.94 | 407  | 0.5491          | 0.86     |
+| 0.1343        | 29.87 | 420  | 0.5528          | 0.86     |
+
+
+### Framework versions
+
+- Transformers 4.39.2
+- Pytorch 1.13.0+cu117
+- Datasets 2.16.1
+- Tokenizers 0.15.1

model.safetensors

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