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flan-t5-large-da-multiwoz_1000
Zekunli/flan-t5-large-da-multiwoz_1000
flan-t5-large-da-multiwoz_1000 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
- Feb 5, 2023
- Updated
- Feb 5, 2023
- SHA
- 081a23fd
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-multiwoz_1000
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: 0.3538
- Accuracy: 41.3747
- Num: 3689
- Gen Len: 15.5115
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: 8
- eval_batch_size: 24
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Num | Gen Len |
|---|---|---|---|---|---|---|
| 1.3315 | 0.24 | 200 | 0.5697 | 25.9543 | 3689 | 14.556 |
| 0.6418 | 0.48 | 400 | 0.4645 | 30.0503 | 3689 | 14.9314 |
| 0.5433 | 0.72 | 600 | 0.4307 | 31.9506 | 3689 | 16.1515 |
| 0.4909 | 0.95 | 800 | 0.4177 | 34.7593 | 3689 | 15.418 |
| 0.4769 | 1.19 | 1000 | 0.3996 | 35.0943 | 3689 | 14.9607 |
| 0.4491 | 1.43 | 1200 | 0.3881 | 36.2741 | 3689 | 15.543 |
| 0.4531 | 1.67 | 1400 | 0.3820 | 35.7704 | 3689 | 14.1583 |
| 0.4322 | 1.91 | 1600 | 0.3726 | 37.4853 | 3689 | 15.961 |
| 0.4188 | 2.15 | 1800 | 0.3699 | 38.4117 | 3689 | 15.0773 |
| 0.4085 | 2.38 | 2000 | 0.3674 | 38.5353 | 3689 | 15.4012 |
| 0.4063 | 2.62 | 2200 | 0.3606 | 40.0046 | 3689 | 15.3546 |
| 0.3977 | 2.86 | 2400 | 0.3570 | 40.6543 | 3689 | 15.704 |
| 0.3992 | 3.1 | 2600 | 0.3549 | 40.4284 | 3689 | 15.7446 |
| 0.3828 | 3.34 | 2800 | 0.3538 | 41.3747 | 3689 | 15.5115 |
| 0.3792 | 3.58 | 3000 | 0.3539 | 39.8513 | 3689 | 14.7951 |
| 0.3914 | 3.81 | 3200 | 0.3498 | 41.0388 | 3689 | 15.4153 |
| 0.3707 | 4.05 | 3400 | 0.3498 | 40.9596 | 3689 | 16.3136 |
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
- Feb 5, 2023
- Updated
- Feb 5, 2023