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--- |
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license: apache-2.0 |
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base_model: moussaKam/barthez-orangesum-abstract |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: barthez-orange-ft |
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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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# barthez-orange-ft |
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This model is a fine-tuned version of [moussaKam/barthez-orangesum-abstract](https://huggingface.co/moussaKam/barthez-orangesum-abstract) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1689 |
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- Rouge1: 0.6719 |
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- Rouge2: 0.6536 |
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- Rougel: 0.6719 |
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- Rougelsum: 0.6722 |
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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: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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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: 20 |
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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 | 31 | 4.6662 | 0.6719 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 1.99 | 62 | 0.6939 | 0.6718 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 2.99 | 93 | 0.2939 | 0.6718 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 3.98 | 124 | 0.2089 | 0.6719 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 4.98 | 155 | 0.1880 | 0.6719 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 5.98 | 186 | 0.1795 | 0.6719 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 6.97 | 217 | 0.1752 | 0.6719 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 8.0 | 249 | 0.1732 | 0.6719 | 0.6535 | 0.6718 | 0.6721 | 20.0 | |
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| No log | 9.0 | 280 | 0.1716 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| No log | 9.99 | 311 | 0.1707 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| No log | 10.99 | 342 | 0.1704 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| No log | 11.98 | 373 | 0.1696 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| No log | 12.98 | 404 | 0.1698 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| No log | 13.98 | 435 | 0.1695 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| No log | 14.97 | 466 | 0.1693 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| No log | 16.0 | 498 | 0.1691 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| 0.9743 | 17.0 | 529 | 0.1691 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| 0.9743 | 17.99 | 560 | 0.1690 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| 0.9743 | 18.99 | 591 | 0.1689 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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| 0.9743 | 19.92 | 620 | 0.1689 | 0.6719 | 0.6536 | 0.6719 | 0.6722 | 20.0 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.13.3 |
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