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idefics-9b-ft-describe-diffusion-bf16-adapter
mrm8488/idefics-9b-ft-describe-diffusion-bf16-adapter
idefics-9b-ft-describe-diffusion-bf16-adapter is a machine learning model from mrm8488. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Sep 4, 2023
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At a glance
- License
- other
- Access
- Public
- Created
- Aug 28, 2023
- Updated
- Sep 4, 2023
- SHA
- d962666f
Base models
Datasets
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. -->
idefics-9b-ft-describe-diffusion-bf16
This model is a fine-tuned version of HuggingFaceM4/idefics-9b on the diffusiondb dataset. It achieves the following results on the evaluation set:
- Loss: 1.4081
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0874 | 0.07 | 50 | 2.1257 |
| 2.0532 | 0.14 | 100 | 1.9973 |
| 1.9417 | 0.21 | 150 | 1.9246 |
| 1.8358 | 0.28 | 200 | 1.8735 |
| 1.8499 | 0.36 | 250 | 1.8305 |
| 1.7695 | 0.43 | 300 | 1.7770 |
| 1.7505 | 0.5 | 350 | 1.7454 |
| 1.713 | 0.57 | 400 | 1.7115 |
| 1.7352 | 0.64 | 450 | 1.6791 |
| 1.6689 | 0.71 | 500 | 1.6526 |
| 1.6183 | 0.78 | 550 | 1.6257 |
| 1.6118 | 0.85 | 600 | 1.6001 |
| 1.6095 | 0.92 | 650 | 1.5800 |
| 1.5598 | 1.0 | 700 | 1.5598 |
| 1.4785 | 1.07 | 750 | 1.5403 |
| 1.4999 | 1.14 | 800 | 1.5219 |
| 1.4589 | 1.21 | 850 | 1.5063 |
| 1.4559 | 1.28 | 900 | 1.4942 |
| 1.4332 | 1.35 | 950 | 1.4792 |
| 1.4859 | 1.42 | 1000 | 1.4658 |
| 1.3888 | 1.49 | 1050 | 1.4537 |
| 1.4032 | 1.56 | 1100 | 1.4445 |
| 1.3702 | 1.64 | 1150 | 1.4352 |
| 1.3625 | 1.71 | 1200 | 1.4276 |
| 1.4067 | 1.78 | 1250 | 1.4199 |
| 1.3829 | 1.85 | 1300 | 1.4149 |
| 1.4251 | 1.92 | 1350 | 1.4103 |
| 1.3619 | 1.99 | 1400 | 1.4081 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- License
- other
- Created
- Aug 28, 2023
- Updated
- Sep 4, 2023