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mt5-small-text-sum-1

Summarization
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PyTorch
TensorBoard
mt5
text2text-generation
Generated from Trainer
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - summarization
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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-small-text-sum-1
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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-small-text-sum-1
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.3715
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+ - Rouge1: 20.75
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+ - Rouge2: 6.54
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+ - Rougel: 20.33
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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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+ - num_epochs: 40
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
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+ | 4.936 | 1.29 | 500 | 2.6226 | 15.38 | 5.14 | 15.22 |
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+ | 3.1573 | 2.58 | 1000 | 2.5081 | 18.02 | 5.53 | 17.8 |
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+ | 2.9258 | 3.87 | 1500 | 2.4499 | 17.19 | 5.3 | 17.0 |
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+ | 2.7786 | 5.15 | 2000 | 2.4264 | 18.17 | 5.02 | 17.99 |
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+ | 2.6786 | 6.44 | 2500 | 2.4088 | 17.98 | 5.48 | 17.6 |
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+ | 2.5824 | 7.73 | 3000 | 2.3909 | 19.43 | 6.32 | 19.07 |
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+ | 2.5261 | 9.02 | 3500 | 2.3691 | 19.06 | 5.94 | 18.76 |
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+ | 2.4372 | 10.31 | 4000 | 2.3580 | 19.76 | 6.37 | 19.49 |
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+ | 2.3727 | 11.6 | 4500 | 2.3595 | 19.96 | 6.52 | 19.68 |
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+ | 2.3488 | 12.89 | 5000 | 2.3580 | 19.63 | 6.14 | 19.31 |
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+ | 2.2868 | 14.18 | 5500 | 2.3595 | 19.93 | 6.4 | 19.72 |
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+ | 2.2268 | 15.46 | 6000 | 2.3632 | 19.95 | 6.13 | 19.55 |
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+ | 2.2081 | 16.75 | 6500 | 2.3631 | 20.47 | 6.34 | 20.1 |
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+ | 2.1583 | 18.04 | 7000 | 2.3562 | 20.04 | 6.13 | 19.71 |
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+ | 2.1178 | 19.33 | 7500 | 2.3615 | 19.55 | 5.8 | 19.1 |
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+ | 2.0904 | 20.62 | 8000 | 2.3549 | 20.37 | 6.6 | 20.05 |
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+ | 2.0697 | 21.91 | 8500 | 2.3859 | 20.53 | 6.64 | 20.22 |
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+ | 2.0256 | 23.2 | 9000 | 2.3715 | 20.75 | 6.54 | 20.33 |
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+ | 2.0011 | 24.48 | 9500 | 2.3713 | 20.55 | 6.72 | 20.25 |
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+ | 1.9899 | 25.77 | 10000 | 2.3582 | 19.82 | 5.82 | 19.4 |
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+ | 1.965 | 27.06 | 10500 | 2.3789 | 20.48 | 5.8 | 20.23 |
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+ | 1.9518 | 28.35 | 11000 | 2.3822 | 20.03 | 6.07 | 19.67 |
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+ | 1.9089 | 29.64 | 11500 | 2.3743 | 19.62 | 6.1 | 19.3 |
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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+cu116
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.2