End of training
Browse files- README.md +80 -0
- model.safetensors +1 -1
- runs/Jan08_11-14-12_d8f0af4aa08e/events.out.tfevents.1704712455.d8f0af4aa08e.2834.1 +3 -0
- runs/Jan08_11-16-05_d8f0af4aa08e/events.out.tfevents.1704712568.d8f0af4aa08e.2834.2 +3 -0
- runs/Jan08_11-21-09_d8f0af4aa08e/events.out.tfevents.1704712871.d8f0af4aa08e.2834.3 +3 -0
- runs/Jan08_11-26-28_d8f0af4aa08e/events.out.tfevents.1704713190.d8f0af4aa08e.2834.4 +3 -0
- training_args.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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datasets:
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- fair_face
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metrics:
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- accuracy
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model-index:
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- name: initial_ViT_model
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: fair_face
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type: fair_face
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config: '0.25'
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split: train[:5000]
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args: '0.25'
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.152
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# initial_ViT_model
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the fair_face dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.1666
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- Accuracy: 0.152
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 256
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.2
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 4.7179 | 3.17 | 50 | 4.5313 | 0.094 |
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| 4.3281 | 6.35 | 100 | 4.2542 | 0.122 |
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| 4.1225 | 9.52 | 150 | 4.1666 | 0.152 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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