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my_t5_small_test
sardelina/my_t5_small_test
my_t5_small_test is a machine learning model from sardelina. 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
- Jun 28, 2024
- Updated
- Jul 2, 2024
- SHA
- f66662ee
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. -->
my_t5_small_test
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4891
- Bleu: 0.0
- Gen Len: 6.8662
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: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 200 | 2.3870 | 0.0 | 6.8375 |
| No log | 2.0 | 400 | 2.2439 | 0.0 | 6.9825 |
| 2.7045 | 3.0 | 600 | 2.1468 | 0.0 | 6.8488 |
| 2.7045 | 4.0 | 800 | 2.0665 | 0.0 | 7.1575 |
| 2.2912 | 5.0 | 1000 | 2.0073 | 0.0 | 7.0238 |
| 2.2912 | 6.0 | 1200 | 1.9477 | 0.0 | 7.3162 |
| 2.2912 | 7.0 | 1400 | 1.8906 | 0.0 | 7.1425 |
| 2.1524 | 8.0 | 1600 | 1.8395 | 0.0 | 7.1438 |
| 2.1524 | 9.0 | 1800 | 1.7949 | 0.0 | 7.1825 |
| 2.032 | 10.0 | 2000 | 1.7475 | 0.0 | 7.0612 |
| 2.032 | 11.0 | 2200 | 1.7084 | 0.0 | 7.0075 |
| 2.032 | 12.0 | 2400 | 1.6749 | 0.0 | 6.9975 |
| 1.9334 | 13.0 | 2600 | 1.6440 | 0.0 | 6.8962 |
| 1.9334 | 14.0 | 2800 | 1.6142 | 0.0 | 7.0388 |
| 1.8689 | 15.0 | 3000 | 1.5895 | 0.0 | 6.9475 |
| 1.8689 | 16.0 | 3200 | 1.5692 | 0.0 | 6.8938 |
| 1.8689 | 17.0 | 3400 | 1.5509 | 0.0 | 6.8538 |
| 1.8137 | 18.0 | 3600 | 1.5340 | 0.0 | 6.8862 |
| 1.8137 | 19.0 | 3800 | 1.5244 | 0.0 | 6.8412 |
| 1.7782 | 20.0 | 4000 | 1.5137 | 0.0 | 6.8712 |
| 1.7782 | 21.0 | 4200 | 1.5053 | 0.0 | 6.8775 |
| 1.7782 | 22.0 | 4400 | 1.4980 | 0.0 | 6.8512 |
| 1.7453 | 23.0 | 4600 | 1.4930 | 0.0 | 6.8638 |
| 1.7453 | 24.0 | 4800 | 1.4901 | 0.0 | 6.8788 |
| 1.7352 | 25.0 | 5000 | 1.4891 | 0.0 | 6.8662 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jun 28, 2024
- Updated
- Jul 2, 2024