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update model card README.md

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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: fine-tuned-QAS-Squad_2-with-xlm-roberta-large
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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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+ # fine-tuned-QAS-Squad_2-with-xlm-roberta-large
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+
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+ This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8615
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+ - Exact Match: 69.2340
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+ - F1: 82.5542
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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: 1e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 128
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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: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
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+ | 1.0967 | 0.5 | 464 | 1.0076 | 57.8908 | 71.8971 |
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+ | 0.912 | 1.0 | 928 | 0.8118 | 65.0306 | 79.0193 |
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+ | 0.8071 | 1.5 | 1392 | 0.7587 | 67.2288 | 80.3986 |
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+ | 0.7414 | 2.0 | 1856 | 0.7322 | 68.3614 | 81.3949 |
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+ | 0.6548 | 2.5 | 2320 | 0.7685 | 67.5896 | 81.3012 |
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+ | 0.624 | 3.0 | 2784 | 0.7307 | 68.5544 | 82.0875 |
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+ | 0.5412 | 3.5 | 3248 | 0.7606 | 69.2340 | 82.4384 |
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+ | 0.5356 | 4.0 | 3712 | 0.7352 | 69.5612 | 82.7509 |
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+ | 0.4463 | 4.5 | 4176 | 0.7862 | 69.2843 | 82.3298 |
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+ | 0.4899 | 5.0 | 4640 | 0.7868 | 69.5109 | 82.7397 |
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+ | 0.417 | 5.5 | 5104 | 0.8615 | 69.2340 | 82.5542 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 2.2.0
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+ - Tokenizers 0.13.2