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End of training

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README.md ADDED
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+ ---
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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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+ - f1
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+ model-index:
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+ - name: roberta-base-detect-cheapfake-combined-train-test-context
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+ results: []
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+ ---
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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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+
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+ # roberta-base-detect-cheapfake-combined-train-test-context
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4470
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+ - Accuracy: 0.78
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+ - F1: 0.7442
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-06
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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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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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 75 | 0.6170 | 0.49 | 0.6577 |
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+ | No log | 2.0 | 150 | 0.4459 | 0.79 | 0.7692 |
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+ | No log | 3.0 | 225 | 0.4441 | 0.79 | 0.7692 |
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+ | No log | 4.0 | 300 | 0.4404 | 0.81 | 0.7865 |
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+ | No log | 5.0 | 375 | 0.4470 | 0.78 | 0.7442 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.0
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+ - Pytorch 2.1.2
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+ - Datasets 2.1.0
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+ - Tokenizers 0.15.1
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+ "layer_norm_eps": 1e-05,
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+ "model_type": "roberta",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ }
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