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peft-finetune-flan-t5-mc-question-generation
Michelvh/peft-finetune-flan-t5-mc-question-generation
peft-finetune-flan-t5-mc-question-generation is a text generation model from Michelvh. Use it when you need the model to write or continue text. 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
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Aug 17, 2023
- Updated
- Sep 26, 2023
- SHA
- 709add2c
Try a prompt
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. -->
peft-finetune-flan-t5-mc-question-generation
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1306
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2907 | 0.13 | 100 | 1.7315 |
| 1.8012 | 0.25 | 200 | 1.3366 |
| 1.5077 | 0.38 | 300 | 1.2346 |
| 1.419 | 0.51 | 400 | 1.2027 |
| 1.3772 | 0.64 | 500 | 1.1884 |
| 1.3566 | 0.76 | 600 | 1.1770 |
| 1.3348 | 0.89 | 700 | 1.1696 |
| 1.3307 | 1.02 | 800 | 1.1624 |
| 1.3247 | 1.15 | 900 | 1.1586 |
| 1.3139 | 1.27 | 1000 | 1.1537 |
| 1.3048 | 1.4 | 1100 | 1.1507 |
| 1.3045 | 1.53 | 1200 | 1.1476 |
| 1.2999 | 1.65 | 1300 | 1.1451 |
| 1.2978 | 1.78 | 1400 | 1.1425 |
| 1.2903 | 1.91 | 1500 | 1.1407 |
| 1.2897 | 2.04 | 1600 | 1.1409 |
| 1.2881 | 2.16 | 1700 | 1.1386 |
| 1.2845 | 2.29 | 1800 | 1.1374 |
| 1.2749 | 2.42 | 1900 | 1.1360 |
| 1.2846 | 2.55 | 2000 | 1.1349 |
| 1.281 | 2.67 | 2100 | 1.1339 |
| 1.282 | 2.8 | 2200 | 1.1331 |
| 1.2786 | 2.93 | 2300 | 1.1326 |
| 1.2799 | 3.06 | 2400 | 1.1322 |
| 1.2777 | 3.18 | 2500 | 1.1320 |
| 1.2767 | 3.31 | 2600 | 1.1316 |
| 1.2716 | 3.44 | 2700 | 1.1313 |
| 1.2762 | 3.56 | 2800 | 1.1309 |
| 1.2723 | 3.69 | 2900 | 1.1305 |
| 1.2741 | 3.82 | 3000 | 1.1304 |
| 1.2762 | 3.95 | 3100 | 1.1306 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
- Task
- Text Generation
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Aug 17, 2023
- Updated
- Sep 26, 2023