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hushem_1x_deit_tiny_adamax_lr0001_fold4

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  1. README.md +111 -0
  2. model.safetensors +1 -1
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-tiny-patch16-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: hushem_1x_deit_tiny_adamax_lr0001_fold4
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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: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8333333333333334
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+ ---
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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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+
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+ # hushem_1x_deit_tiny_adamax_lr0001_fold4
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5599
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+ - Accuracy: 0.8333
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 0.1
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.67 | 1 | 1.6749 | 0.3095 |
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+ | No log | 2.0 | 3 | 1.3545 | 0.3333 |
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+ | No log | 2.67 | 4 | 1.3451 | 0.2857 |
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+ | No log | 4.0 | 6 | 1.2535 | 0.5238 |
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+ | No log | 4.67 | 7 | 1.2290 | 0.4286 |
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+ | No log | 6.0 | 9 | 1.1555 | 0.5 |
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+ | 1.2457 | 6.67 | 10 | 1.0938 | 0.5 |
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+ | 1.2457 | 8.0 | 12 | 0.9608 | 0.4762 |
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+ | 1.2457 | 8.67 | 13 | 0.8825 | 0.5952 |
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+ | 1.2457 | 10.0 | 15 | 0.7678 | 0.7143 |
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+ | 1.2457 | 10.67 | 16 | 0.7184 | 0.7857 |
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+ | 1.2457 | 12.0 | 18 | 0.6658 | 0.7619 |
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+ | 1.2457 | 12.67 | 19 | 0.6361 | 0.7619 |
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+ | 0.4167 | 14.0 | 21 | 0.6247 | 0.8095 |
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+ | 0.4167 | 14.67 | 22 | 0.6111 | 0.7857 |
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+ | 0.4167 | 16.0 | 24 | 0.5896 | 0.7857 |
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+ | 0.4167 | 16.67 | 25 | 0.5886 | 0.7381 |
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+ | 0.4167 | 18.0 | 27 | 0.6107 | 0.7619 |
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+ | 0.4167 | 18.67 | 28 | 0.6198 | 0.7619 |
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+ | 0.0627 | 20.0 | 30 | 0.6194 | 0.7619 |
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+ | 0.0627 | 20.67 | 31 | 0.6092 | 0.7619 |
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+ | 0.0627 | 22.0 | 33 | 0.5917 | 0.7857 |
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+ | 0.0627 | 22.67 | 34 | 0.5871 | 0.7857 |
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+ | 0.0627 | 24.0 | 36 | 0.5872 | 0.8095 |
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+ | 0.0627 | 24.67 | 37 | 0.5896 | 0.8095 |
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+ | 0.0627 | 26.0 | 39 | 0.5921 | 0.8095 |
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+ | 0.0081 | 26.67 | 40 | 0.5908 | 0.8095 |
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+ | 0.0081 | 28.0 | 42 | 0.5818 | 0.8095 |
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+ | 0.0081 | 28.67 | 43 | 0.5772 | 0.8095 |
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+ | 0.0081 | 30.0 | 45 | 0.5685 | 0.8095 |
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+ | 0.0081 | 30.67 | 46 | 0.5654 | 0.8095 |
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+ | 0.0081 | 32.0 | 48 | 0.5614 | 0.8333 |
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+ | 0.0081 | 32.67 | 49 | 0.5603 | 0.8333 |
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+ | 0.0038 | 33.33 | 50 | 0.5599 | 0.8333 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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