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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-cstop_artificial
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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-cstop_artificial
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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: 0.1292
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+ - Exact Match: 0.3399
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 32
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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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+ | 2.08 | 28.5 | 200 | 0.3320 | 0.0376 |
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+ | 0.272 | 57.13 | 400 | 0.1084 | 0.2630 |
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+ | 0.0789 | 85.63 | 600 | 0.0830 | 0.3184 |
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+ | 0.0355 | 114.25 | 800 | 0.0816 | 0.3363 |
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+ | 0.0207 | 142.75 | 1000 | 0.0868 | 0.3292 |
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+ | 0.014 | 171.38 | 1200 | 0.0952 | 0.3399 |
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+ | 0.0099 | 199.88 | 1400 | 0.1089 | 0.3381 |
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+ | 0.0076 | 228.5 | 1600 | 0.1104 | 0.3381 |
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+ | 0.0057 | 257.13 | 1800 | 0.1153 | 0.3292 |
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+ | 0.0048 | 285.63 | 2000 | 0.1153 | 0.3327 |
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+ | 0.004 | 314.25 | 2200 | 0.1206 | 0.3363 |
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+ | 0.0032 | 342.75 | 2400 | 0.1229 | 0.3363 |
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+ | 0.0028 | 371.38 | 2600 | 0.1268 | 0.3381 |
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+ | 0.0023 | 399.88 | 2800 | 0.1288 | 0.3399 |
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+ | 0.002 | 428.5 | 3000 | 0.1292 | 0.3399 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.1
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+ - Pytorch 1.13.0+cu117
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+ - Datasets 2.7.1
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+ - Tokenizers 0.13.2