Marcos12886
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Browse files- README.md +11 -7
- checkpoint-111/trainer_state.json +18 -18
- checkpoint-111/training_args.bin +1 -1
- checkpoint-126/trainer_state.json +21 -21
- checkpoint-126/training_args.bin +1 -1
- checkpoint-18/model.safetensors +1 -1
- checkpoint-18/optimizer.pt +1 -1
- checkpoint-18/scheduler.pt +1 -1
- checkpoint-18/trainer_state.json +6 -6
- checkpoint-18/training_args.bin +1 -1
- checkpoint-37/model.safetensors +1 -1
- checkpoint-37/optimizer.pt +1 -1
- checkpoint-37/scheduler.pt +1 -1
- checkpoint-37/trainer_state.json +12 -12
- checkpoint-37/training_args.bin +1 -1
- checkpoint-55/trainer_state.json +9 -9
- checkpoint-55/training_args.bin +1 -1
- checkpoint-74/trainer_state.json +12 -12
- checkpoint-74/training_args.bin +1 -1
- checkpoint-93/trainer_state.json +15 -15
- checkpoint-93/training_args.bin +1 -1
- model.safetensors +1 -1
- runs/Sep04_19-03-05_ubumarcos/events.out.tfevents.1725469387.ubumarcos +3 -0
- runs/Sep04_19-03-44_ubumarcos/events.out.tfevents.1725469427.ubumarcos +3 -0
- training_args.bin +1 -1
README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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 audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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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 |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| No log | 0.9664 | 18 | 0.
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| No log | 1.9866 | 37 | 0.
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| No log | 2.
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8691275167785235
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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 audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3360
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- Accuracy: 0.8691
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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: 7
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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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| No log | 0.9664 | 18 | 0.6860 | 0.7584 |
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| No log | 1.9866 | 37 | 0.4623 | 0.8020 |
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| No log | 2.9530 | 55 | 0.4069 | 0.8188 |
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| No log | 3.9732 | 74 | 0.3811 | 0.8356 |
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| No log | 4.9933 | 93 | 0.3542 | 0.8356 |
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| No log | 5.9597 | 111 | 0.3380 | 0.8658 |
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| No log | 6.7651 | 126 | 0.3360 | 0.8691 |
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### Framework versions
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