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dit-base-rvlcdip-finetuned-grp-actual
Tidzo/dit-base-rvlcdip-finetuned-grp-actual
dit-base-rvlcdip-finetuned-grp-actual is a image classification model from Tidzo. Use it when you need a label for an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- Model type
- beit
- Access
- Public
- Created
- Aug 26, 2023
- Updated
- Oct 17, 2023
- SHA
- a6ddc99f
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. -->
dit-base-rvlcdip-finetuned-grp-actual
This model is a fine-tuned version of microsoft/dit-base-finetuned-rvlcdip on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4601
- Accuracy: 0.9015
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8692 | 0.96 | 18 | 0.6972 | 0.8561 |
| 0.7348 | 1.97 | 37 | 0.6350 | 0.8598 |
| 0.6655 | 2.99 | 56 | 0.5339 | 0.8712 |
| 0.7167 | 4.0 | 75 | 0.5046 | 0.8902 |
| 0.694 | 4.96 | 93 | 0.5026 | 0.8864 |
| 0.6638 | 5.97 | 112 | 0.4601 | 0.9015 |
| 0.6618 | 6.72 | 126 | 0.4582 | 0.8977 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- beit
- Created
- Aug 26, 2023
- Updated
- Oct 17, 2023