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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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+ 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-base-downstream-ildc
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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-ildc
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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: 0.7039
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+ - Accuracy: 0.5
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+ - Precision: 0.0
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+ - Recall: 0.0
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+ - 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: 8
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+ - eval_batch_size: 8
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+ - seed: 1
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 32
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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: 20.0
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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 | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|
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+ | 0.6863 | 1.0 | 1010 | 0.7004 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6812 | 2.0 | 2020 | 0.6994 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6816 | 3.0 | 3030 | 0.7515 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6796 | 4.0 | 4040 | 0.7039 | 0.5 | 0.0 | 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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