First summarizer model
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: google-t5/t5-small
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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: google-t5-summarizer
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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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# google-t5-summarizer
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3654
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- Rouge1: 0.1892
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- Rouge2: 0.0938
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- Rougel: 0.1604
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- Rougelsum: 0.1604
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- Gen Len: 20.0
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## Model description
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More information needed
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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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## 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: 2e-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_FUSED 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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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| No log | 1.0 | 124 | 2.6000 | 0.1394 | 0.0499 | 0.1158 | 0.1159 | 20.0 |
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| No log | 2.0 | 248 | 2.4289 | 0.1666 | 0.0747 | 0.1407 | 0.1404 | 20.0 |
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| No log | 3.0 | 372 | 2.3809 | 0.1846 | 0.09 | 0.1562 | 0.1562 | 20.0 |
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| No log | 4.0 | 496 | 2.3654 | 0.1892 | 0.0938 | 0.1604 | 0.1604 | 20.0 |
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### Framework versions
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- Transformers 4.57.1
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- Pytorch 2.9.0
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- Datasets 4.2.0
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- Tokenizers 0.22.1
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