T5Model_for_Ecommerce
This model is a fine-tuned version of Praveen76/FinetunedT5Model on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9462
- Rouge1: 0.0406
- Rouge2: 0.0272
- Rougel: 0.0345
- Rougelsum: 0.0344
- Gen Len: 1.9352
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 | 4.2817 | 0.2641 | 0.1401 | 0.2239 | 0.2236 | 19.0 |
No log | 2.0 | 54 | 1.2657 | 0.0685 | 0.0411 | 0.0583 | 0.0589 | 4.0463 |
No log | 3.0 | 81 | 1.1014 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 4.0 | 108 | 1.0864 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 5.0 | 135 | 1.0668 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 6.0 | 162 | 1.0474 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 7.0 | 189 | 1.0204 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 8.0 | 216 | 1.0035 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 9.0 | 243 | 0.9870 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 10.0 | 270 | 0.9732 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 11.0 | 297 | 0.9625 | 0.0098 | 0.0059 | 0.0094 | 0.0094 | 0.5278 |
No log | 12.0 | 324 | 0.9563 | 0.0295 | 0.0194 | 0.0266 | 0.0264 | 1.4074 |
No log | 13.0 | 351 | 0.9504 | 0.0325 | 0.0213 | 0.0291 | 0.029 | 1.5833 |
No log | 14.0 | 378 | 0.9472 | 0.0406 | 0.0272 | 0.0345 | 0.0344 | 1.9352 |
No log | 15.0 | 405 | 0.9462 | 0.0406 | 0.0272 | 0.0345 | 0.0344 | 1.9352 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.