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End of training

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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-base
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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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+ - sacrebleu
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+ model-index:
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+ - name: mT5-TextSimp-LT-BatchSize8-lr1e-4
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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-TextSimp-LT-BatchSize8-lr1e-4
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+
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+ This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0826
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+ - Rouge1: 0.6956
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+ - Rouge2: 0.532
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+ - Rougel: 0.6875
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+ - Sacrebleu: 41.0349
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+ - Gen Len: 38.0501
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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: 0.0001
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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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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 8
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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 | Sacrebleu | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | 22.5133 | 0.96 | 200 | 14.4822 | 0.0057 | 0.0 | 0.0056 | 0.0013 | 512.0 |
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+ | 1.0276 | 1.91 | 400 | 0.7352 | 0.022 | 0.0005 | 0.0215 | 0.0232 | 41.4702 |
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+ | 0.6477 | 2.87 | 600 | 1.5193 | 0.1021 | 0.012 | 0.0954 | 0.0573 | 83.3723 |
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+ | 0.1784 | 3.83 | 800 | 0.1149 | 0.6014 | 0.4222 | 0.5898 | 32.2723 | 38.0501 |
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+ | 0.158 | 4.78 | 1000 | 0.0930 | 0.6546 | 0.4822 | 0.6463 | 37.3842 | 38.0501 |
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+ | 0.1059 | 5.74 | 1200 | 0.0884 | 0.6714 | 0.4983 | 0.6635 | 39.0129 | 38.0501 |
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+ | 0.1542 | 6.7 | 1400 | 0.0830 | 0.688 | 0.5184 | 0.6803 | 40.419 | 38.0501 |
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+ | 0.1206 | 7.66 | 1600 | 0.0826 | 0.6956 | 0.532 | 0.6875 | 41.0349 | 38.0501 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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