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README.md ADDED
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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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+ model-index:
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+ - name: roberta-base-downstream-eurlex
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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-downstream-eurlex
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+
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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: 0.1732
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+ - Macro-f1: 0.0
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+ - Micro-f1: 0.0
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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: 3e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 1
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+ - distributed_type: multi-GPU
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+ - num_devices: 2
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+ - total_train_batch_size: 256
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+ - total_eval_batch_size: 256
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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: 2.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Macro-f1 | Micro-f1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | No log | 1.0 | 215 | 0.1769 | 0.0 | 0.0 |
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+ | No log | 2.0 | 430 | 0.1732 | 0.0 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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