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---
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tags:
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- generated_from_trainer
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datasets:
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- govreport-summarization
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model-index:
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- name: Pegasus-x-base-govreport-12288-1024-numepoch-10
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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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# Pegasus-x-base-govreport-12288-1024-numepoch-10
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This model is a fine-tuned version of [google/pegasus-x-base](https://huggingface.co/google/pegasus-x-base) on the govreport-summarization dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6234
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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: 0.0001
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- train_batch_size: 1
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 64
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- total_train_batch_size: 64
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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 |
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|:-------------:|:-----:|:----:|:---------------:|
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| 2.1149 | 0.37 | 100 | 1.9237 |
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| 1.9545 | 0.73 | 200 | 1.8380 |
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| 1.8835 | 1.1 | 300 | 1.7574 |
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| 1.862 | 1.46 | 400 | 1.7305 |
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| 1.8536 | 1.83 | 500 | 1.7100 |
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| 1.8062 | 2.19 | 600 | 1.6944 |
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| 1.8161 | 2.56 | 700 | 1.6882 |
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| 1.7611 | 2.92 | 800 | 1.6803 |
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| 1.7878 | 3.29 | 900 | 1.6671 |
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| 1.7299 | 3.65 | 1000 | 1.6599 |
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| 1.7636 | 4.02 | 1100 | 1.6558 |
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| 1.7262 | 4.38 | 1200 | 1.6547 |
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| 1.715 | 4.75 | 1300 | 1.6437 |
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| 1.7178 | 5.12 | 1400 | 1.6445 |
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| 1.7163 | 5.48 | 1500 | 1.6386 |
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| 1.7367 | 5.85 | 1600 | 1.6364 |
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| 1.7114 | 6.21 | 1700 | 1.6365 |
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| 1.6452 | 6.58 | 1800 | 1.6309 |
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| 1.7251 | 6.94 | 1900 | 1.6301 |
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| 1.6726 | 7.31 | 2000 | 1.6305 |
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| 1.7104 | 7.67 | 2100 | 1.6285 |
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| 1.6739 | 8.04 | 2200 | 1.6252 |
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| 1.7082 | 8.4 | 2300 | 1.6246 |
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| 1.6888 | 8.77 | 2400 | 1.6244 |
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| 1.6609 | 9.13 | 2500 | 1.6256 |
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| 1.6707 | 9.5 | 2600 | 1.6241 |
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| 1.669 | 9.86 | 2700 | 1.6234 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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