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Transfer Learning Finetuned Gtzan Model

This model is a fine-tuned version of sanchit-gandhi/distilhubert-finetuned-gtzan on an unknown dataset. It achieves the following results on the evaluation set: Loss: 1.3704 Accuracy: 0.5565 F1: 0.5318

Fontehuggingface.co/balamaniansp/transfer-learning-finetuned-gtzan-model/tree/dc4a3200063f5e80af2e23273aeb793b3e85d692
TipoOtherModelo basesanchit-gandhi/distilhubert-finetuned-gtzanVersãoRevision dc4a320Cnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
90,4 MB
Modelo base
sanchit-gandhi/distilhubert-finetuned-gtzan
Versão
vRevision dc4a320
Atualizado
22 de set. de 2026
Downloads
3
Fonte
Hugging Face

Descrição da fonte

transfer-learning-finetuned-gtzan-model

This model is a fine-tuned version of sanchit-gandhi/distilhubert-finetuned-gtzan on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3704
  • Accuracy: 0.5565
  • F1: 0.5318

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: 2e-05
  • train_batch_size: 32
  • 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: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15
  • mixed_precision_training: Native AMP
  • label_smoothing_factor: 0.05

Training results

Training LossEpochStepValidation LossAccuracyF1
1.91030.47355001.96920.28230.2697
1.67530.947010001.71290.39920.3692
1.46131.420515001.63540.42400.3987
1.42261.893920001.54260.45040.4267
1.39092.367425001.51760.47020.4423
1.39192.840930001.49440.48550.4584
1.25773.314435001.44660.49550.4710
1.24553.787940001.45010.50500.4833
1.12614.261445001.44600.49450.4757
1.11174.734850001.44530.50870.4812
1.05915.208355001.46480.50320.4738
1.0795.681860001.39120.52880.4998
1.00716.155365001.39560.52850.5012
0.9766.628870001.40030.53090.5049
0.95177.102375001.40350.53430.5079
0.98737.575880001.36960.53830.5140
0.86718.049285001.38140.54460.5217
0.85468.522790001.37880.54460.5173
0.99458.996295001.37960.54540.5229
0.8579.4697100001.36670.55300.5293
0.87039.9432105001.34390.55360.5292
0.801810.4167110001.36540.55540.5296
0.833310.8902115001.36960.54910.5235
0.828211.3636120001.38250.55120.5245
0.719311.8371125001.37580.55540.5296
0.736612.3106130001.35820.55940.5326
0.79212.7841135001.38290.55120.5262
0.775813.2576140001.36840.55880.5340
0.863113.7311145001.36630.55800.5325
0.826114.2045150001.37520.55620.5310
0.762414.6780155001.37040.55650.5318

Framework versions

  • Transformers 4.57.1
  • Pytorch 2.8.0+cu126
  • Datasets 4.4.2
  • Tokenizers 0.22.1

Fontes

1 fonte
Hugging FacePrimárioVersão dc4a3200063f5e80af2e23273aeb793b3e85d692
huggingface.co/balamaniansp/transfer-learning-finetuned-gtzan-model/tree/dc4a3200063f5e80af2e23273aeb793b3e85d692

Verificado 6 de set.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 90,4 MB · SHA-256 1457bb032b70…351f · Hugging Face

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Trechos de fonte

2 trechos
Readme6 de set.huggingface.co/balamaniansp/transfer-learning-finetuned-gtzan-model

--- library_name: transformers license: apache-2.0 base_model: sanchit-gandhi/distilhubert-finetuned-gtzan tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: transfer-learning-finetuned-gtzan-model 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. --> # transfer-learning-finetuned-gtzan-model This model is a fine-tuned version of [sanchit-gandhi/distilhubert-finetuned-gtzan](https://huggingface.co/sanchit-gandhi/distilhubert-finetuned-gtzan) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.3704 - Accuracy: 0.5565 - F1: 0.5318 ## 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: 2e-05 - train_batch_size: 32 - 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: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 15 - mixed_precision_training: Native AMP - label_smoothing_factor: 0.05 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:| | 1.9103 | 0.4735 | 500 | 1.9692 | 0.2823 | 0.2697 | | 1.6753 | 0.9470 | 1000 | 1.7129 | 0.3992 | 0.3692 | | 1.4613 | 1.4205 | 1500 | 1.6354 | 0.4240 | 0.3987 | | 1.4226 | 1.8939 | 2000 | 1.5426 | 0.4504 | 0.4267 | | 1.3909 | 2.3674 | 2500 | 1.5176 | 0.4702 | 0.4423 | | 1.3919 | 2.8409 | 3000 | 1.4944 | 0.4855 | 0.4584 | | 1.2577 | 3.3144 | 3500 | 1.4466 | 0.4955 | 0.4710 | | 1.2455 | 3.7879 | 4000 | 1.4501 | 0.5050 | 0.4833 | | 1.1261 | 4.2614 | 4500 | 1.4460 | 0.4945 | 0.4757 | | 1.1117 | 4.7348 | 5000 | 1.4453 | 0.5087 | 0.4812 | | 1.0591 | 5.2083 | 5500 | 1.4648 | 0.5032 | 0.4738 | | 1.079 | 5.6818 | 6000 | 1.3912 | 0.5288 | 0.4998 | | 1.0071 | 6.1553 | 6500 | 1.3956 | 0.5285 | 0.5012 | | 0.976 | 6.6288 | 7000 | 1.4003 | 0.5309 | 0.5049 | | 0.9517 | 7.1023 | 7500 | 1.4035 | 0.5343 | 0.5079 | | 0.9873 | 7.5758 | 8000 | 1.36...

Note6 de set.huggingface.co/balamaniansp/transfer-learning-finetuned-gtzan-model

Source context: 3 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo balamaniansp/transfer-learning-finetuned-gtzan-model