Marcos12886
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End of training
Browse files
README.md
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- generated_from_trainer
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datasets:
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- audiofolder
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model-index:
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- name: distilhubert-finetuned-mixed-data
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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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# distilhubert-finetuned-mixed-data
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
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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: cosine
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- lr_scheduler_warmup_ratio: 0.001
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| No log | 0.9664 | 18 | 0.
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### Framework versions
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- generated_from_trainer
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datasets:
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- audiofolder
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: distilhubert-finetuned-mixed-data
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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: audiofolder
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type: audiofolder
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config: default
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split: None
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.889261744966443
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- name: F1
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type: f1
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value: 0.8885260378939167
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- name: Precision
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type: precision
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value: 0.887959005693052
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- name: Recall
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type: recall
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value: 0.889261744966443
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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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# distilhubert-finetuned-mixed-data
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3033
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- Accuracy: 0.8893
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- F1: 0.8885
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- Precision: 0.8880
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- Recall: 0.8893
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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: cosine
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- lr_scheduler_warmup_ratio: 0.001
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| No log | 0.9664 | 18 | 0.6703 | 0.7819 | 0.7264 | 0.6898 | 0.7819 |
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| No log | 1.9866 | 37 | 0.5053 | 0.7752 | 0.7203 | 0.6849 | 0.7752 |
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| No log | 2.9530 | 55 | 0.4473 | 0.7987 | 0.7457 | 0.7193 | 0.7987 |
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| No log | 3.9732 | 74 | 0.3820 | 0.8691 | 0.8578 | 0.8854 | 0.8691 |
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| No log | 4.9933 | 93 | 0.3435 | 0.8691 | 0.8671 | 0.8704 | 0.8691 |
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| No log | 5.9597 | 111 | 0.3176 | 0.8859 | 0.8855 | 0.8868 | 0.8859 |
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| No log | 6.9799 | 130 | 0.3045 | 0.8859 | 0.8853 | 0.8850 | 0.8859 |
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| No log | 8.0 | 149 | 0.3051 | 0.8859 | 0.8849 | 0.8843 | 0.8859 |
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| No log | 8.9664 | 167 | 0.3031 | 0.8926 | 0.8913 | 0.8910 | 0.8926 |
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| No log | 9.6644 | 180 | 0.3033 | 0.8893 | 0.8885 | 0.8880 | 0.8893 |
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### Framework versions
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model.safetensors
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runs/Sep02_13-16-04_ubumarcos/events.out.tfevents.1725275766.ubumarcos
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training_args.bin
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