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t5-small-finetuned-medical_knowledge_from_extracts
alraisi/t5-small-finetuned-medical_knowledge_from_extracts
t5-small-finetuned-medical_knowledge_from_extracts is a machine learning model from alraisi. 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
- Feb 5, 2024
- Updated
- Feb 5, 2024
- SHA
- 8e3d1d3a
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-small-finetuned-medical_knowledge_from_extracts
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1561
- Rouge1: 32.9864
- Rouge2: 13.23
- Rougel: 32.3943
- Rougelsum: 32.4479
- 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: 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 87 | 1.7900 | 22.2671 | 0.7152 | 21.395 | 21.4052 | 19.0 |
| No log | 2.0 | 174 | 1.4078 | 31.5412 | 9.5847 | 31.1049 | 31.1295 | 18.9986 |
| No log | 3.0 | 261 | 1.3030 | 32.0827 | 11.4061 | 31.531 | 31.5738 | 19.0 |
| No log | 4.0 | 348 | 1.2511 | 32.3393 | 11.8795 | 31.7307 | 31.7918 | 19.0 |
| No log | 5.0 | 435 | 1.2163 | 33.0328 | 12.6708 | 32.4155 | 32.4638 | 19.0 |
| 1.7948 | 6.0 | 522 | 1.1927 | 32.9176 | 12.915 | 32.3593 | 32.3931 | 19.0 |
| 1.7948 | 7.0 | 609 | 1.1757 | 32.809 | 12.932 | 32.263 | 32.3132 | 19.0 |
| 1.7948 | 8.0 | 696 | 1.1642 | 32.9525 | 13.0878 | 32.3805 | 32.4297 | 19.0 |
| 1.7948 | 9.0 | 783 | 1.1582 | 32.9297 | 13.1084 | 32.3697 | 32.4219 | 19.0 |
| 1.7948 | 10.0 | 870 | 1.1561 | 32.9864 | 13.23 | 32.3943 | 32.4479 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Feb 5, 2024
- Updated
- Feb 5, 2024