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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: uitnlp/visobert
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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: ViSoBERT_Domain_classifier
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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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+ # ViSoBERT_Domain_classifier
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+
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+ This model is a fine-tuned version of [uitnlp/visobert](https://huggingface.co/uitnlp/visobert) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0735
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+ - Accuracy: 0.9842
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use adamw_torch 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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+ - num_epochs: 3
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 302 | 0.0537 | 0.9807 |
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+ | 0.0737 | 2.0 | 604 | 0.0565 | 0.9839 |
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+ | 0.0737 | 3.0 | 906 | 0.0735 | 0.9842 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.51.3
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.0
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