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--- |
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license: mit |
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base_model: october-sd/bart-large-xsum-finetuned-en-sum |
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tags: |
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- summarization |
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- generated_from_trainer |
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model-index: |
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- name: bart-large-xsum-finetuned-en-sum-2 |
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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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# bart-large-xsum-finetuned-en-sum-2 |
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This model is a fine-tuned version of [october-sd/bart-large-xsum-finetuned-en-sum](https://huggingface.co/october-sd/bart-large-xsum-finetuned-en-sum) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6259 |
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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: 5e-06 |
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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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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 512 |
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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: 2 |
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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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| No log | 0.99 | 126 | 1.6222 | |
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| No log | 1.98 | 252 | 1.6259 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.2 |
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