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--- |
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license: mit |
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base_model: facebook/bart-large-xsum |
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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: reddit_summarization_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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# reddit_summarization_model |
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This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co./facebook/bart-large-xsum) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9410 |
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- Rouge1: 0.4169 |
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- Rouge2: 0.163 |
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- Rougel: 0.276 |
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- Rougelsum: 0.3001 |
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- Gen Len: 61.6276 |
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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: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 9 |
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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: 5 |
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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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| 1.9905 | 1.0 | 972 | 1.8412 | 0.412 | 0.1593 | 0.2725 | 0.2965 | 61.7025 | |
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| 1.5293 | 2.0 | 1944 | 1.8022 | 0.4162 | 0.1634 | 0.2766 | 0.2998 | 61.6673 | |
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| 1.2934 | 3.0 | 2916 | 1.8352 | 0.4194 | 0.1641 | 0.2789 | 0.3019 | 61.548 | |
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| 1.1481 | 4.0 | 3888 | 1.8898 | 0.415 | 0.1623 | 0.2753 | 0.2985 | 61.5825 | |
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| 1.04 | 5.0 | 4860 | 1.9410 | 0.4169 | 0.163 | 0.276 | 0.3001 | 61.6276 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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