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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: LIAMF-USP/roberta-large-finetuned-race
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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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+ - precision
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+ - recall
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+ model-index:
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+ - name: roberta-mqa
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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-mqa
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+
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+ This model is a fine-tuned version of [LIAMF-USP/roberta-large-finetuned-race](https://huggingface.co/LIAMF-USP/roberta-large-finetuned-race) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6094
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+ - Accuracy: 0.2120
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+ - F1: 0.1945
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+ - Precision: 0.2027
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+ - Recall: 0.2057
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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: 8
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+ - eval_batch_size: 16
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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: 3
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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 | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.6124 | 1.0 | 3712 | 1.6094 | 0.2079 | 0.1810 | 0.1981 | 0.2006 |
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+ | 1.613 | 2.0 | 7424 | 1.6094 | 0.2077 | 0.0871 | 0.1713 | 0.1975 |
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+ | 1.61 | 3.0 | 11136 | 1.6094 | 0.2120 | 0.1945 | 0.2027 | 0.2057 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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