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update model card README.md

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: t5-small-pointer-adv-mtop
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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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+ # t5-small-pointer-adv-mtop
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+
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+ This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1341
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+ - Exact Match: 0.4541
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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: 0.001
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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: 64
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+ - total_train_batch_size: 512
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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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+ - training_steps: 3000
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------:|
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+ | 2.1628 | 1.09 | 200 | 0.7205 | 0.0022 |
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+ | 1.1208 | 2.17 | 400 | 0.6393 | 0.0013 |
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+ | 0.8675 | 3.26 | 600 | 0.5905 | 0.0027 |
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+ | 1.8729 | 4.35 | 800 | 0.5726 | 0.0031 |
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+ | 3.5417 | 5.43 | 1000 | 0.5371 | 0.0067 |
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+ | 0.9087 | 6.52 | 1200 | 0.3512 | 0.1119 |
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+ | 1.2224 | 7.61 | 1400 | 0.2739 | 0.1911 |
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+ | 0.7597 | 8.69 | 1600 | 0.2151 | 0.3016 |
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+ | 0.6981 | 9.78 | 1800 | 0.1736 | 0.3749 |
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+ | 0.4779 | 10.87 | 2000 | 0.1548 | 0.4166 |
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+ | 0.4397 | 11.96 | 2200 | 0.1377 | 0.4510 |
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+ | 0.4101 | 13.04 | 2400 | 0.1480 | 0.4197 |
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+ | 0.3323 | 14.13 | 2600 | 0.1396 | 0.4398 |
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+ | 0.2565 | 15.22 | 2800 | 0.1351 | 0.4523 |
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+ | 0.2108 | 16.3 | 3000 | 0.1341 | 0.4541 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.24.0
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+ - Pytorch 1.13.0+cu117
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+ - Datasets 2.7.0
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+ - Tokenizers 0.13.2