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flan-t5-large-da-multiwoz2.0_80-ep50-nonstop
Zekunli/flan-t5-large-da-multiwoz2.0_80-ep50-nonstop
flan-t5-large-da-multiwoz2.0_80-ep50-nonstop is a machine learning model from Zekunli. 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
- Apr 15, 2023
- Updated
- Apr 15, 2023
- SHA
- 639ee2cf
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. -->
flan-t5-large-da-multiwoz2.0_80-ep50-nonstop
This model is a fine-tuned version of google/flan-t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5512
- Accuracy: 35.6401
- Num: 7358
- Gen Len: 15.8543
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: 128
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Num | Gen Len |
|---|---|---|---|---|---|---|
| 0.863 | 10.81 | 400 | 0.4586 | 33.763 | 7358 | 15.9868 |
| 0.3719 | 21.62 | 800 | 0.4596 | 35.5769 | 7358 | 15.9114 |
| 0.2806 | 32.43 | 1200 | 0.5168 | 36.033 | 7358 | 15.9323 |
| 0.2316 | 43.24 | 1600 | 0.5392 | 35.7188 | 7358 | 15.8434 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Apr 15, 2023
- Updated
- Apr 15, 2023