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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-efficient-tiny-nh8 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: t5-efficient-tiny-nh8-summarizer |
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results: [] |
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datasets: |
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- shorecode/summary-collection-60k-rows |
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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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# t5-efficient-tiny-nh8-summarizer |
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This model is a fine-tuned version of [google/t5-efficient-tiny-nh8](https://huggingface.co/google/t5-efficient-tiny-nh8) on shorecode/summary-collection-60k-rows. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7583 |
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## Model description |
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A general purpose text summarizer |
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## Intended uses & limitations |
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A general purpose text summarizer |
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## Training and evaluation data |
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Trained and evaluated on shorecode/summary-collection-60k-rows |
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## Training procedure |
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Trained using the Gradio SDK on Hugging Face Spaces using shared Zero GPU(s) |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 7.000000000000001e-05 |
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- train_batch_size: 70 |
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- eval_batch_size: 70 |
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- seed: 42 |
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- optimizer: Use 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: 3 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.1522 | 0.2328 | 200 | 0.9863 | |
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| 0.9677 | 0.4657 | 400 | 0.9158 | |
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| 0.9143 | 0.6985 | 600 | 0.8762 | |
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| 0.8894 | 0.9313 | 800 | 0.8478 | |
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| 0.8586 | 1.1641 | 1000 | 0.8262 | |
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| 0.8382 | 1.3970 | 1200 | 0.8079 | |
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| 0.8198 | 1.6298 | 1400 | 0.7938 | |
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| 0.805 | 1.8626 | 1600 | 0.7823 | |
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| 0.8035 | 2.0955 | 1800 | 0.7727 | |
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| 0.7897 | 2.3283 | 2000 | 0.7661 | |
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| 0.7849 | 2.5611 | 2200 | 0.7607 | |
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| 0.7781 | 2.7939 | 2400 | 0.7583 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.21.0 |
