Marcos12886
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End of training
Browse files- README.md +3 -42
- model.safetensors +1 -1
- runs/Sep02_11-59-10_ubumarcos/events.out.tfevents.1725271162.ubumarcos +3 -0
- runs/Sep02_12-01-00_ubumarcos/events.out.tfevents.1725271267.ubumarcos +3 -0
- runs/Sep02_13-43-36_ubumarcos/events.out.tfevents.1725277433.ubumarcos +3 -0
- runs/Sep02_13-48-37_ubumarcos/events.out.tfevents.1725277727.ubumarcos +3 -0
- training_args.bin +1 -1
README.md
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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-cry-detector
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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: train
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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: 0.991941391941392
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- name: F1
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type: f1
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value: 0.9919569277165429
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- name: Precision
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type: precision
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value: 0.9920048531706146
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- name: Recall
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type: recall
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value: 0.991941391941392
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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-cry-detector
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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: 0.0408
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- Accuracy: 0.9919
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- F1: 0.9920
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- Precision: 0.9920
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- Recall: 0.9919
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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 | 0.9956 | 85 | 0.
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| No log | 1.9912 | 170 | 0.0680 | 0.9758 | 0.9760 | 0.9770 | 0.9758 |
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| No log | 2.9985 | 256 | 0.0447 | 0.9875 | 0.9876 | 0.9876 | 0.9875 |
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| No log | 3.9941 | 341 | 0.0452 | 0.9905 | 0.9905 | 0.9905 | 0.9905 |
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| No log | 4.9898 | 426 | 0.0439 | 0.9919 | 0.9920 | 0.9920 | 0.9919 |
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| 0.053 | 5.9971 | 512 | 0.0401 | 0.9919 | 0.9920 | 0.9920 | 0.9919 |
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| 0.053 | 6.9693 | 595 | 0.0408 | 0.9919 | 0.9920 | 0.9920 | 0.9919 |
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### Framework versions
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datasets:
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- audiofolder
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model-index:
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- name: distilhubert-finetuned-cry-detector
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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-cry-detector
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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: 1
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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 | 0.9956 | 85 | 0.1014 | 0.9641 | 0.9642 | 0.9643 | 0.9641 |
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### Framework versions
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model.safetensors
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