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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: microsoft/deberta-v3-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: deberta-v3-base-finetuned-autext23_s2
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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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+ # deberta-v3-base-finetuned-autext23_s2
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0620
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+ - Accuracy: 0.5731
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+ - F1: 0.5648
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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: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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 | 246 | 0.9935 | 0.5587 | 0.5371 |
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+ | 1.1328 | 2.0 | 492 | 0.9254 | 0.5792 | 0.5592 |
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+ | 1.1328 | 3.0 | 738 | 0.9501 | 0.5801 | 0.5692 |
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+ | 0.7267 | 4.0 | 984 | 1.0345 | 0.5619 | 0.5509 |
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+ | 0.7267 | 5.0 | 1230 | 1.0620 | 0.5731 | 0.5648 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ "_name_or_path": "microsoft/deberta-v3-base",
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+ "DebertaV2ForSequenceClassification"
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+ "layer_norm_eps": 1e-07,
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+ "model_type": "deberta-v2",
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