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--- |
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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: Text_Summarization_model_15042024 |
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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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# Text_Summarization_model_15042024 |
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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: 1.5948 |
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- Rouge1: 0.2374 |
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- Rouge2: 0.1905 |
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- Rougel: 0.2302 |
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- Rougelsum: 0.2302 |
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- Gen Len: 19.0 |
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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: 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: 15 |
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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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| 2.4344 | 0.5 | 500 | 1.9250 | 0.2184 | 0.1678 | 0.2088 | 0.2088 | 18.9925 | |
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| 2.0598 | 1.0 | 1000 | 1.8118 | 0.2247 | 0.1755 | 0.2155 | 0.2155 | 18.9955 | |
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| 1.9648 | 1.5 | 1500 | 1.7581 | 0.2303 | 0.1802 | 0.2206 | 0.2206 | 19.0 | |
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| 1.9119 | 2.0 | 2000 | 1.7214 | 0.2315 | 0.1822 | 0.2221 | 0.2221 | 19.0 | |
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| 1.8624 | 2.5 | 2500 | 1.6953 | 0.2337 | 0.185 | 0.2253 | 0.2253 | 19.0 | |
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| 1.8508 | 3.0 | 3000 | 1.6769 | 0.2346 | 0.186 | 0.2266 | 0.2266 | 19.0 | |
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| 1.8092 | 3.5 | 3500 | 1.6563 | 0.2353 | 0.1871 | 0.2278 | 0.2279 | 19.0 | |
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| 1.8065 | 4.0 | 4000 | 1.6377 | 0.2359 | 0.188 | 0.2284 | 0.2284 | 19.0 | |
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| 1.7724 | 4.5 | 4500 | 1.6309 | 0.237 | 0.1895 | 0.2297 | 0.2298 | 19.0 | |
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| 1.7703 | 5.0 | 5000 | 1.6165 | 0.2376 | 0.1899 | 0.2302 | 0.2303 | 19.0 | |
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| 1.7468 | 5.5 | 5500 | 1.6082 | 0.2374 | 0.1902 | 0.2303 | 0.2303 | 19.0 | |
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| 1.7347 | 6.0 | 6000 | 1.5992 | 0.2374 | 0.1906 | 0.2303 | 0.2304 | 19.0 | |
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| 1.7162 | 6.5 | 6500 | 1.5948 | 0.2374 | 0.1905 | 0.2302 | 0.2302 | 19.0 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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