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Browse files- README.md +73 -0
- model.safetensors +1 -1
README.md
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---
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license: apache-2.0
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base_model: asapp/sew-mid-100k
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: sew-ft-fake-detection
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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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should probably proofread and complete it, then remove this comment. -->
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# sew-ft-fake-detection
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This model is a fine-tuned version of [asapp/sew-mid-100k](https://huggingface.co/asapp/sew-mid-100k) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6278
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- Accuracy: 0.7439
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 16
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- seed: 0
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 10.0
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- mixed_precision_training: Native AMP
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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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| 0.6344 | 0.9851 | 33 | 0.6395 | 0.6505 |
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| 0.6157 | 2.0 | 67 | 0.6703 | 0.5215 |
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| 0.5572 | 2.9851 | 100 | 0.5615 | 0.7131 |
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| 0.4968 | 4.0 | 134 | 0.8149 | 0.6944 |
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| 0.4988 | 4.9851 | 167 | 0.8099 | 0.7037 |
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| 0.4756 | 6.0 | 201 | 0.8319 | 0.7103 |
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| 0.4334 | 6.9851 | 234 | 0.7317 | 0.7336 |
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| 0.4321 | 8.0 | 268 | 0.6548 | 0.7383 |
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| 0.4436 | 8.9851 | 301 | 0.6232 | 0.7439 |
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| 0.4493 | 9.8507 | 330 | 0.6278 | 0.7439 |
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### Framework versions
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- Transformers 4.41.0.dev0
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- Pytorch 2.1.0a0+32f93b1
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
CHANGED
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version https://git-lfs.github.com/spec/v1
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-
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size 699537900
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version https://git-lfs.github.com/spec/v1
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size 699537900
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