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BARTModel_for_Ecommerce
Praveen76/BARTModel_for_Ecommerce
BARTModel_for_Ecommerce is a machine learning model from Praveen76. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- Dec 4, 2023
- Updated
- Dec 4, 2023
- SHA
- 33c31d32
Base models
Model card
From the Hugging Face model README
<!-- 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 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6511
- Rouge1: 0.35
- Rouge2: 0.2527
- Rougel: 0.3229
- Rougelsum: 0.323
- 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 | 3.3125 | 0.2888 | 0.1482 | 0.2448 | 0.2454 | 20.0 |
| No log | 2.0 | 54 | 2.2699 | 0.2926 | 0.1667 | 0.2564 | 0.2574 | 20.0 |
| No log | 3.0 | 81 | 1.7686 | 0.3119 | 0.1908 | 0.2752 | 0.2753 | 20.0 |
| No log | 4.0 | 108 | 1.3882 | 0.324 | 0.2104 | 0.2937 | 0.2939 | 20.0 |
| No log | 5.0 | 135 | 1.1275 | 0.3151 | 0.2061 | 0.2871 | 0.2877 | 20.0 |
| No log | 6.0 | 162 | 0.9372 | 0.3293 | 0.2231 | 0.3017 | 0.3022 | 20.0 |
| No log | 7.0 | 189 | 0.8252 | 0.33 | 0.2182 | 0.2982 | 0.2988 | 20.0 |
| No log | 8.0 | 216 | 0.7575 | 0.3378 | 0.2317 | 0.3058 | 0.3065 | 20.0 |
| No log | 9.0 | 243 | 0.7102 | 0.3498 | 0.2418 | 0.3148 | 0.3149 | 20.0 |
| No log | 10.0 | 270 | 0.6890 | 0.3411 | 0.2374 | 0.3119 | 0.3126 | 20.0 |
| No log | 11.0 | 297 | 0.6760 | 0.3441 | 0.2394 | 0.3151 | 0.3155 | 20.0 |
| No log | 12.0 | 324 | 0.6640 | 0.3442 | 0.2417 | 0.3151 | 0.3152 | 20.0 |
| No log | 13.0 | 351 | 0.6520 | 0.3548 | 0.2506 | 0.3242 | 0.3246 | 20.0 |
| No log | 14.0 | 378 | 0.6519 | 0.3497 | 0.2506 | 0.3199 | 0.3201 | 20.0 |
| No log | 15.0 | 405 | 0.6511 | 0.35 | 0.2527 | 0.3229 | 0.323 | 20.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Dec 4, 2023
- Updated
- Dec 4, 2023