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README.md
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---
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license: apache-2.0
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: facebook/bart-large
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metrics:
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- rouge
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model-index:
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- name: bart-large-samsum-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-samsum-2
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This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4648
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- Rouge1: 0.4729
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- Rouge2: 0.2361
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- Rougel: 0.3953
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- Rougelsum: 0.3947
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- Gen Len: 18.0
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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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: 10
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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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| No log | 1.0 | 460 | 1.5889 | 0.4523 | 0.2142 | 0.3714 | 0.3708 | 18.0 |
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| 2.2048 | 2.0 | 921 | 1.5293 | 0.4642 | 0.231 | 0.3875 | 0.3871 | 18.0 |
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| 1.765 | 3.0 | 1381 | 1.4971 | 0.4662 | 0.2268 | 0.3864 | 0.3857 | 18.0 |
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| 1.7019 | 4.0 | 1842 | 1.4893 | 0.471 | 0.2337 | 0.3934 | 0.3925 | 18.0 |
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| 1.6734 | 5.0 | 2302 | 1.4844 | 0.4725 | 0.2338 | 0.3945 | 0.3937 | 18.0 |
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| 1.6536 | 6.0 | 2763 | 1.4707 | 0.4717 | 0.2341 | 0.3935 | 0.3928 | 18.0 |
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| 1.6493 | 7.0 | 3223 | 1.4746 | 0.4736 | 0.2357 | 0.3956 | 0.3947 | 18.0 |
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| 1.6363 | 8.0 | 3684 | 1.4688 | 0.4731 | 0.2344 | 0.3937 | 0.393 | 18.0 |
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| 1.6337 | 9.0 | 4144 | 1.4658 | 0.4725 | 0.2345 | 0.3937 | 0.393 | 18.0 |
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| 1.6283 | 9.99 | 4600 | 1.4648 | 0.4729 | 0.2361 | 0.3953 | 0.3947 | 18.0 |
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### Framework versions
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- PEFT 0.10.1.dev0
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- Transformers 4.39.3
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- Pytorch 2.2.2
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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