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--- |
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license: apache-2.0 |
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base_model: facebook/bart-base |
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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: BARTModel_for_Ecommerce |
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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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# BARTModel_for_Ecommerce |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6511 |
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- Rouge1: 0.35 |
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- Rouge2: 0.2527 |
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- Rougel: 0.3229 |
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- Rougelsum: 0.323 |
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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: 16 |
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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: 15 |
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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 | 27 | 3.3125 | 0.2888 | 0.1482 | 0.2448 | 0.2454 | 20.0 | |
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| No log | 2.0 | 54 | 2.2699 | 0.2926 | 0.1667 | 0.2564 | 0.2574 | 20.0 | |
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| No log | 3.0 | 81 | 1.7686 | 0.3119 | 0.1908 | 0.2752 | 0.2753 | 20.0 | |
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| No log | 4.0 | 108 | 1.3882 | 0.324 | 0.2104 | 0.2937 | 0.2939 | 20.0 | |
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| No log | 5.0 | 135 | 1.1275 | 0.3151 | 0.2061 | 0.2871 | 0.2877 | 20.0 | |
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| No log | 6.0 | 162 | 0.9372 | 0.3293 | 0.2231 | 0.3017 | 0.3022 | 20.0 | |
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| No log | 7.0 | 189 | 0.8252 | 0.33 | 0.2182 | 0.2982 | 0.2988 | 20.0 | |
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| No log | 8.0 | 216 | 0.7575 | 0.3378 | 0.2317 | 0.3058 | 0.3065 | 20.0 | |
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| No log | 9.0 | 243 | 0.7102 | 0.3498 | 0.2418 | 0.3148 | 0.3149 | 20.0 | |
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| No log | 10.0 | 270 | 0.6890 | 0.3411 | 0.2374 | 0.3119 | 0.3126 | 20.0 | |
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| No log | 11.0 | 297 | 0.6760 | 0.3441 | 0.2394 | 0.3151 | 0.3155 | 20.0 | |
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| No log | 12.0 | 324 | 0.6640 | 0.3442 | 0.2417 | 0.3151 | 0.3152 | 20.0 | |
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| No log | 13.0 | 351 | 0.6520 | 0.3548 | 0.2506 | 0.3242 | 0.3246 | 20.0 | |
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| No log | 14.0 | 378 | 0.6519 | 0.3497 | 0.2506 | 0.3199 | 0.3201 | 20.0 | |
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| No log | 15.0 | 405 | 0.6511 | 0.35 | 0.2527 | 0.3229 | 0.323 | 20.0 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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