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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: shorecode/t5-efficient-tiny-nh8-summarizer |
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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 [shorecode/t5-efficient-tiny-nh8-summarizer](https://huggingface.co/shorecode/t5-efficient-tiny-nh8-summarizer) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6597 |
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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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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: 0.00015000000000000001 |
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- train_batch_size: 63 |
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- eval_batch_size: 63 |
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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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| 1.0837 | 0.2663 | 200 | 0.9227 | |
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| 0.9027 | 0.5326 | 400 | 0.8449 | |
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| 0.842 | 0.7989 | 600 | 0.7949 | |
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| 0.7971 | 1.0652 | 800 | 0.7585 | |
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| 0.768 | 1.3316 | 1000 | 0.7288 | |
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| 0.7359 | 1.5979 | 1200 | 0.7069 | |
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| 0.7145 | 1.8642 | 1400 | 0.6898 | |
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| 0.7047 | 2.1305 | 1600 | 0.6773 | |
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| 0.6926 | 2.3968 | 1800 | 0.6678 | |
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| 0.6855 | 2.6631 | 2000 | 0.6620 | |
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| 0.68 | 2.9294 | 2200 | 0.6597 | |
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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 |
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