Training completed on Modal A100
Browse files- README.md +71 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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license: mit
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base_model: roberta-base
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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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- precision
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- recall
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- f1
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model-index:
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- name: roberta-detector-v2
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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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# roberta-detector-v2
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0271
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- Accuracy: 0.9942
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- Precision: 0.9943
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- Recall: 0.9942
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- F1: 0.9942
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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: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3
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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 | Precision | Recall | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.0226 | 1.0 | 5997 | 0.0339 | 0.9925 | 0.9925 | 0.9925 | 0.9925 |
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| 0.0208 | 2.0 | 11994 | 0.0271 | 0.9942 | 0.9943 | 0.9942 | 0.9942 |
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| 0.0097 | 3.0 | 17991 | 0.0392 | 0.9936 | 0.9937 | 0.9936 | 0.9936 |
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### Framework versions
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- Transformers 4.55.2
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- Pytorch 2.8.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.21.4
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 498612824
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version https://git-lfs.github.com/spec/v1
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size 498612824
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