| --- |
| license: apache-2.0 |
| base_model: facebook/bart-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: BARTModel_for_Ecommerce |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # BARTModel_for_Ecommerce |
|
|
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6400 |
| - Rouge1: 0.3515 |
| - Rouge2: 0.2381 |
| - Rougel: 0.3187 |
| - Rougelsum: 0.3187 |
| - Gen Len: 20.0 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 27 | 3.5206 | 0.3072 | 0.1595 | 0.26 | 0.26 | 20.0 | |
| | No log | 2.0 | 54 | 2.3786 | 0.3139 | 0.1747 | 0.268 | 0.2681 | 20.0 | |
| | No log | 3.0 | 81 | 1.8443 | 0.3328 | 0.2038 | 0.2924 | 0.2932 | 20.0 | |
| | No log | 4.0 | 108 | 1.4537 | 0.3276 | 0.2076 | 0.2887 | 0.2892 | 20.0 | |
| | No log | 5.0 | 135 | 1.1480 | 0.3301 | 0.212 | 0.292 | 0.2924 | 20.0 | |
| | No log | 6.0 | 162 | 0.9457 | 0.3465 | 0.2292 | 0.3084 | 0.3091 | 20.0 | |
| | No log | 7.0 | 189 | 0.8317 | 0.345 | 0.2253 | 0.3074 | 0.3078 | 20.0 | |
| | No log | 8.0 | 216 | 0.7544 | 0.3456 | 0.2293 | 0.3121 | 0.3124 | 20.0 | |
| | No log | 9.0 | 243 | 0.7076 | 0.3601 | 0.246 | 0.3278 | 0.3276 | 20.0 | |
| | No log | 10.0 | 270 | 0.6817 | 0.3464 | 0.2358 | 0.3139 | 0.3139 | 20.0 | |
| | No log | 11.0 | 297 | 0.6609 | 0.3586 | 0.2407 | 0.3235 | 0.3241 | 20.0 | |
| | No log | 12.0 | 324 | 0.6557 | 0.3563 | 0.2432 | 0.3226 | 0.3227 | 20.0 | |
| | No log | 13.0 | 351 | 0.6451 | 0.3511 | 0.238 | 0.3192 | 0.3195 | 20.0 | |
| | No log | 14.0 | 378 | 0.6430 | 0.3516 | 0.2385 | 0.3182 | 0.3183 | 20.0 | |
| | No log | 15.0 | 405 | 0.6400 | 0.3515 | 0.2381 | 0.3187 | 0.3187 | 20.0 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.0 |
| - Tokenizers 0.15.0 |
|
|
