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- README.md +14 -39
- config.json +1 -1
- pytorch_model.bin +2 -2
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.gitignore
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checkpoint-*/
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README.md
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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- name: distilhubert-finetuned-gtzan
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: GTZAN
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type: marsyas/gtzan
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config: all
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split: train
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args: all
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.84
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.951 | 1.0 | 113 | 1.7690 | 0.38 |
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| 1.3034 | 2.0 | 226 | 1.1612 | 0.67 |
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| 1.0602 | 3.0 | 339 | 0.9306 | 0.81 |
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| 0.7441 | 4.0 | 452 | 0.7898 | 0.8 |
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| 0.5939 | 5.0 | 565 | 0.6638 | 0.81 |
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| 0.3561 | 6.0 | 678 | 0.6515 | 0.79 |
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| 0.3599 | 7.0 | 791 | 0.5987 | 0.8 |
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| 0.1462 | 8.0 | 904 | 0.6281 | 0.81 |
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| 0.1511 | 9.0 | 1017 | 0.5793 | 0.84 |
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| 0.152 | 10.0 | 1130 | 0.6278 | 0.84 |
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### Framework versions
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- Transformers 4.
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- Pytorch 2.1
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- Datasets 2.14.
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- Tokenizers 0.
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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model-index:
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- name: distilhubert-finetuned-gtzan
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.4784
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- eval_accuracy: 0.87
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- eval_runtime: 52.0685
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- eval_samples_per_second: 1.921
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- eval_steps_per_second: 0.25
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- epoch: 7.0
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- step: 791
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- Accuracy: 0.87
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 15
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.1
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- Tokenizers 0.13.3
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config.json
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"num_hidden_layers": 2,
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"pad_token_id": 0,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_weighted_layer_sum": false,
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"vocab_size": 32
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}
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"num_hidden_layers": 2,
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"pad_token_id": 0,
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"torch_dtype": "float32",
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"use_weighted_layer_sum": false,
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