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--- |
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license: apache-2.0 |
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base_model: 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: summarizer_samsum_model |
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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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# summarizer_samsum_model |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3992 |
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- Rouge1: 0.4144 |
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- Rouge2: 0.1805 |
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- Rougel: 0.3419 |
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- Rougelsum: 0.3418 |
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- Gen Len: 16.6732 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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- mixed_precision_training: Native AMP |
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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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| 0.4595 | 1.0 | 737 | 0.4170 | 0.3923 | 0.163 | 0.3243 | 0.3242 | 16.1826 | |
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| 0.4474 | 2.0 | 1474 | 0.4113 | 0.3991 | 0.1685 | 0.3304 | 0.3303 | 16.5925 | |
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| 0.4416 | 3.0 | 2211 | 0.4092 | 0.4021 | 0.1722 | 0.3337 | 0.3339 | 16.6023 | |
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| 0.4388 | 4.0 | 2948 | 0.4048 | 0.4062 | 0.1737 | 0.3361 | 0.3361 | 16.5731 | |
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| 0.4331 | 5.0 | 3685 | 0.4030 | 0.4093 | 0.1758 | 0.3379 | 0.338 | 16.696 | |
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| 0.4243 | 6.0 | 4422 | 0.4010 | 0.4111 | 0.1778 | 0.3396 | 0.3396 | 16.5728 | |
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| 0.4234 | 7.0 | 5159 | 0.4000 | 0.4129 | 0.1789 | 0.3406 | 0.3405 | 16.7139 | |
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| 0.425 | 8.0 | 5896 | 0.3996 | 0.4125 | 0.1797 | 0.3407 | 0.3407 | 16.7089 | |
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| 0.4247 | 9.0 | 6633 | 0.3993 | 0.4147 | 0.181 | 0.3421 | 0.3422 | 16.6943 | |
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| 0.4176 | 10.0 | 7370 | 0.3992 | 0.4144 | 0.1805 | 0.3419 | 0.3418 | 16.6732 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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