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Model save

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/mt5-large
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: mt5-large-finetuned-scope-summarization
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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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+ # mt5-large-finetuned-scope-summarization
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+
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+ This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 7.7968
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+ - Rouge1: 8.9288
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+ - Rouge2: 2.5195
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+ - Rougel: 8.1326
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+ - Rougelsum: 8.2266
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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: 5.6e-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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+ - 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
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
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+ | 24.9681 | 1.0 | 13 | 14.1263 | 9.679 | 1.2781 | 9.2044 | 9.2028 |
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+ | 19.4912 | 2.0 | 26 | 13.8332 | 10.3322 | 2.2934 | 10.0898 | 9.9917 |
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+ | 18.9675 | 3.0 | 39 | 14.5743 | 10.644 | 2.4553 | 10.4176 | 10.3855 |
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+ | 23.2647 | 4.0 | 52 | 16.1424 | 9.4387 | 1.9352 | 8.8508 | 8.8573 |
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+ | 25.5379 | 5.0 | 65 | 16.1511 | 8.9967 | 2.3549 | 8.6046 | 8.666 |
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+ | 23.0787 | 6.0 | 78 | 15.0432 | 9.4838 | 2.3778 | 9.0507 | 9.1552 |
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+ | 20.5359 | 7.0 | 91 | 12.4876 | 8.9692 | 2.5655 | 8.5533 | 8.6442 |
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+ | 18.6638 | 8.0 | 104 | 10.5506 | 10.5377 | 2.5387 | 9.4585 | 9.3817 |
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+ | 15.6668 | 9.0 | 117 | 10.4213 | 11.1515 | 2.3781 | 10.5545 | 10.6241 |
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+ | 16.0823 | 10.0 | 130 | 9.7474 | 11.3564 | 2.6133 | 10.5169 | 10.5736 |
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+ | 16.189 | 11.0 | 143 | 9.3992 | 10.5378 | 3.3175 | 9.2739 | 9.4737 |
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+ | 14.6943 | 12.0 | 156 | 9.1679 | 9.8364 | 2.942 | 8.991 | 9.0988 |
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+ | 13.9725 | 13.0 | 169 | 9.4899 | 9.1523 | 2.6655 | 8.499 | 8.6962 |
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+ | 14.0998 | 14.0 | 182 | 8.4480 | 9.7567 | 2.9029 | 8.2077 | 8.3139 |
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+ | 13.2 | 15.0 | 195 | 8.2385 | 9.9148 | 2.9029 | 8.1975 | 8.3074 |
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+ | 13.1084 | 16.0 | 208 | 8.0442 | 8.1004 | 2.2435 | 7.4792 | 7.5977 |
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+ | 13.6186 | 17.0 | 221 | 7.9349 | 8.2995 | 2.2435 | 7.4792 | 7.5977 |
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+ | 12.6013 | 18.0 | 234 | 7.8921 | 8.5692 | 2.5238 | 7.7018 | 7.8229 |
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+ | 12.8011 | 19.0 | 247 | 7.8561 | 8.5692 | 2.5238 | 7.7018 | 7.8229 |
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+ | 12.9507 | 20.0 | 260 | 7.7968 | 8.9288 | 2.5195 | 8.1326 | 8.2266 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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