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t5-fine-tuning
HeavenlyJoe/t5-fine-tuning
t5-fine-tuning is a machine learning model from HeavenlyJoe. 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
- Nov 21, 2023
- Updated
- Nov 21, 2023
- SHA
- 4eb487db
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. -->
t5-fine-tuning
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4274
- Bleu: 0.1699
- Gen Len: 19.0
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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 | Bleu | Gen Len |
|---|---|---|---|---|---|
| 3.9901 | 0.44 | 25 | 3.3580 | 0.5345 | 18.9005 |
| 3.4338 | 0.88 | 50 | 3.1131 | 0.227 | 19.0 |
| 3.2615 | 1.32 | 75 | 2.9891 | 0.1444 | 19.0 |
| 3.1286 | 1.75 | 100 | 2.8978 | 0.1767 | 19.0 |
| 3.0565 | 2.19 | 125 | 2.8249 | 0.1813 | 19.0 |
| 2.963 | 2.63 | 150 | 2.7604 | 0.1566 | 19.0 |
| 2.9233 | 3.07 | 175 | 2.7123 | 0.1815 | 19.0 |
| 2.8678 | 3.51 | 200 | 2.6672 | 0.1564 | 19.0 |
| 2.8132 | 3.95 | 225 | 2.6269 | 0.1746 | 19.0 |
| 2.7812 | 4.39 | 250 | 2.5950 | 0.1573 | 19.0 |
| 2.7436 | 4.82 | 275 | 2.5690 | 0.1841 | 19.0 |
| 2.7031 | 5.26 | 300 | 2.5425 | 0.2019 | 19.0 |
| 2.6841 | 5.7 | 325 | 2.5212 | 0.1956 | 19.0 |
| 2.6859 | 6.14 | 350 | 2.5053 | 0.1478 | 19.0 |
| 2.6585 | 6.58 | 375 | 2.4855 | 0.1754 | 19.0 |
| 2.6153 | 7.02 | 400 | 2.4720 | 0.1697 | 19.0 |
| 2.594 | 7.46 | 425 | 2.4600 | 0.1696 | 19.0 |
| 2.6114 | 7.89 | 450 | 2.4476 | 0.1685 | 19.0 |
| 2.5904 | 8.33 | 475 | 2.4413 | 0.1664 | 19.0 |
| 2.5829 | 8.77 | 500 | 2.4337 | 0.1675 | 19.0 |
| 2.5683 | 9.21 | 525 | 2.4304 | 0.1634 | 19.0 |
| 2.5731 | 9.65 | 550 | 2.4274 | 0.1699 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Nov 21, 2023
- Updated
- Nov 21, 2023