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nvl-ca
veerganesh/nvl-ca
nvl-ca is a machine learning model from veerganesh. 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
- Dec 16, 2023
- Updated
- Dec 16, 2023
- SHA
- ebf1b641
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. -->
nvl-ca
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6425
- Rouge1: 36.2683
- Rouge2: 17.3571
- Rougel: 31.414
- Rougelsum: 33.3573
- Gen Len: 18.1
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7351 | 1.0 | 50 | 2.0532 | 29.1549 | 10.8095 | 24.5213 | 27.1706 | 18.54 |
| 2.2954 | 2.0 | 100 | 1.8884 | 34.1103 | 15.1143 | 28.6964 | 30.6995 | 18.5 |
| 2.1461 | 3.0 | 150 | 1.7999 | 33.7268 | 15.3397 | 29.1248 | 30.7545 | 18.48 |
| 2.0402 | 4.0 | 200 | 1.7510 | 35.2811 | 16.3829 | 29.5922 | 31.3828 | 18.64 |
| 1.9727 | 5.0 | 250 | 1.7251 | 35.9939 | 17.0171 | 30.9116 | 32.514 | 18.3 |
| 1.9185 | 6.0 | 300 | 1.6982 | 36.1673 | 17.3892 | 31.4179 | 33.2171 | 18.06 |
| 1.8791 | 7.0 | 350 | 1.6809 | 36.0791 | 17.9475 | 31.6153 | 33.2867 | 18.2 |
| 1.8443 | 8.0 | 400 | 1.6631 | 36.3616 | 17.7432 | 31.9719 | 33.651 | 17.96 |
| 1.8322 | 9.0 | 450 | 1.6533 | 35.9061 | 16.9737 | 31.1291 | 33.1402 | 17.96 |
| 1.7978 | 10.0 | 500 | 1.6482 | 35.8366 | 17.0094 | 31.3893 | 33.3356 | 17.88 |
| 1.8037 | 11.0 | 550 | 1.6440 | 36.2683 | 17.3571 | 31.414 | 33.3573 | 18.1 |
| 1.7937 | 12.0 | 600 | 1.6425 | 36.2683 | 17.3571 | 31.414 | 33.3573 | 18.1 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Dec 16, 2023
- Updated
- Dec 16, 2023