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product_recommendation
anushakamath/product_recommendation
product_recommendation is a machine learning model from anushakamath. 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
- t5
- Access
- Public
- Created
- Jul 14, 2023
- Updated
- Jul 14, 2023
- SHA
- 29c8d53a
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. -->
product_recommendation
This model is a fine-tuned version of t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4953
- Rouge1: 73.0159
- Rouge2: 66.6667
- Rougel: 72.2222
- Rougelsum: 72.2222
- Gen Len: 4.1905
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 0.96 | 6 | 0.4314 | 60.3175 | 47.6190 | 59.8413 | 60.3175 | 4.1429 |
| No log | 1.96 | 12 | 0.4339 | 52.6984 | 38.0952 | 53.1746 | 52.3810 | 4.0952 |
| No log | 2.96 | 18 | 0.5350 | 65.0794 | 52.3810 | 64.2857 | 64.9206 | 4.4286 |
| No log | 3.96 | 24 | 0.3075 | 72.8571 | 61.9048 | 72.1429 | 72.1429 | 4.1905 |
| No log | 4.96 | 30 | 0.4016 | 74.6032 | 66.6667 | 74.6032 | 75.3968 | 4.3333 |
| No log | 5.96 | 36 | 0.4496 | 76.1905 | 71.4286 | 74.6032 | 74.6032 | 4.1905 |
| No log | 6.96 | 42 | 0.5539 | 60.3175 | 57.1429 | 61.9048 | 60.3175 | 4.0 |
| No log | 7.96 | 48 | 0.3816 | 80.9524 | 76.1905 | 79.3651 | 79.3651 | 4.1905 |
| No log | 8.96 | 54 | 0.4602 | 74.6032 | 71.4286 | 74.6032 | 74.6032 | 4.1429 |
| No log | 9.96 | 60 | 0.4953 | 73.0159 | 66.6667 | 72.2222 | 72.2222 | 4.1905 |
Framework versions
- Transformers 4.26.0
- Pytorch 2.0.1+cu118
- Datasets 2.8.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jul 14, 2023
- Updated
- Jul 14, 2023