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--- |
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base_model: allenai/PRIMERA-multinews |
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library_name: peft |
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metrics: |
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- rouge |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: PRIMERA-multinews-lora-finetuned |
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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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# PRIMERA-multinews-lora-finetuned |
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This model is a fine-tuned version of [allenai/PRIMERA-multinews](https://huggingface.co/allenai/PRIMERA-multinews) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6767 |
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- Rouge1: 13.1661 |
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- Rouge2: 6.075 |
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- Rougel: 11.1948 |
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- Rougelsum: 12.1382 |
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- Gen Len: 20.0 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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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: 16 |
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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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| 2.2385 | 1.0 | 4725 | 1.9183 | 15.8308 | 7.6039 | 12.6624 | 14.1866 | 20.0 | |
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| 2.1419 | 2.0 | 9450 | 1.8933 | 14.8545 | 6.8893 | 12.144 | 13.4623 | 20.0 | |
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| 2.1286 | 3.0 | 14175 | 1.8619 | 16.2585 | 8.1431 | 13.4226 | 14.8653 | 20.0 | |
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| 2.0669 | 4.0 | 18900 | 1.8129 | 15.9624 | 7.5293 | 13.3809 | 14.7765 | 20.0 | |
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| 2.0448 | 5.0 | 23625 | 1.7636 | 16.2801 | 8.045 | 13.6178 | 14.996 | 20.0 | |
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| 1.9831 | 6.0 | 28350 | 1.7037 | 13.8735 | 5.9956 | 10.8251 | 12.2545 | 20.0 | |
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| 1.9926 | 7.0 | 33075 | 1.7623 | 13.9591 | 5.8861 | 11.112 | 12.4349 | 20.0 | |
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| 1.99 | 8.0 | 37800 | 1.7247 | 13.1441 | 5.2565 | 10.7117 | 11.851 | 20.0 | |
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| 1.9495 | 9.0 | 42525 | 1.7065 | 12.4863 | 4.6444 | 10.0155 | 11.3874 | 20.0 | |
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| 1.9782 | 10.0 | 47250 | 1.6919 | 11.8394 | 4.0068 | 9.4554 | 10.6421 | 20.0 | |
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| 1.9087 | 11.0 | 51975 | 1.6910 | 13.011 | 5.5644 | 10.7255 | 11.8532 | 20.0 | |
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| 1.9693 | 12.0 | 56700 | 1.6872 | 13.2678 | 5.7966 | 11.0537 | 12.1103 | 20.0 | |
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| 1.9445 | 13.0 | 61425 | 1.7084 | 13.2757 | 5.9337 | 11.084 | 12.2354 | 20.0 | |
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| 1.9467 | 14.0 | 66150 | 1.6729 | 12.9202 | 5.424 | 10.5315 | 11.6661 | 20.0 | |
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| 1.9582 | 15.0 | 70875 | 1.6786 | 13.2851 | 6.0806 | 11.291 | 12.2518 | 20.0 | |
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| 1.9186 | 16.0 | 75600 | 1.6767 | 13.1661 | 6.075 | 11.1948 | 12.1382 | 20.0 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
