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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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## Evaluation Score |
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**'ROUGE'**: |
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{ |
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'rouge1': 0.5012, |
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'rouge2': 0.2205, |
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'rougeL': 0.2552, |
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'rougeLsum': 0.2554 |
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} |
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**'BERT_SCORE'** |
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{'f1': 0.859, |
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'precision': 0.8619, |
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'recall': 0.8563 |
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} |
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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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