| ---
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| library_name: transformers
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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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| - 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-finetuned-summarize
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| results: []
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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-finetuned-summarize
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| This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: nan
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| - Rouge1: 0.0
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| - Rouge2: 0.0
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| - Rougel: 0.0
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| - Rougelsum: 0.0
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|
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| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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| More information needed
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| ## Training and evaluation data
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| More information needed
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|
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| ## Training procedure
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| ### Training hyperparameters
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| The following hyperparameters were used during training:
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| - learning_rate: 5e-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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| - lr_scheduler_type: linear
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| - num_epochs: 20
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| - mixed_precision_training: Native AMP
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|
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| ### Training results
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| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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| |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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| | 0.0 | 0.9875 | 79 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 1.975 | 158 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 2.9625 | 237 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 3.95 | 316 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 4.9375 | 395 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 5.925 | 474 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 6.9125 | 553 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 7.9 | 632 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 8.8875 | 711 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 9.875 | 790 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 10.8625 | 869 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 11.85 | 948 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 12.8375 | 1027 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 13.825 | 1106 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 14.8125 | 1185 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 15.8 | 1264 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 16.7875 | 1343 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 17.775 | 1422 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 18.7625 | 1501 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| | 0.0 | 19.75 | 1580 | nan | 0.0 | 0.0 | 0.0 | 0.0 |
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| ### Framework versions
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|
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| - Transformers 4.47.1
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| - Pytorch 2.5.1+cu121
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| - Datasets 3.2.0
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| - Tokenizers 0.21.0
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|
