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t-5_small_test_3
jgibb/t-5_small_test_3
t-5_small_test_3 is a machine learning model from jgibb. 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
- Mar 13, 2024
- Updated
- Mar 13, 2024
- SHA
- 2a1a1e8a
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. -->
t-5_small_test_3
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5645
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.09 | 250 | 1.7997 |
| 2.4572 | 0.18 | 500 | 1.6985 |
| 2.4572 | 0.27 | 750 | 1.6370 |
| 1.7999 | 0.35 | 1000 | 1.6171 |
| 1.7999 | 0.44 | 1250 | 1.5987 |
| 1.7654 | 0.53 | 1500 | 1.5850 |
| 1.7654 | 0.62 | 1750 | 1.5795 |
| 1.6833 | 0.71 | 2000 | 1.5732 |
| 1.6833 | 0.8 | 2250 | 1.5690 |
| 1.6961 | 0.89 | 2500 | 1.5659 |
| 1.6961 | 0.98 | 2750 | 1.5645 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 13, 2024
- Updated
- Mar 13, 2024