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hushem_1x_deit_tiny_adamax_lr001_fold2

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  1. README.md +111 -0
  2. model.safetensors +1 -1
  3. runs/Nov10_11-45-33_95f6e207dd34/events.out.tfevents.1699616733.95f6e207dd34.1398.1 +2 -2
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_lr001_fold2
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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: 0.5333333333333333
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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_lr001_fold2
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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: 1.4814
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+ - Accuracy: 0.5333
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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: 0.001
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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 | 4.5182 | 0.2444 |
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+ | No log | 2.0 | 3 | 1.5416 | 0.2444 |
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+ | No log | 2.67 | 4 | 1.5662 | 0.2667 |
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+ | No log | 4.0 | 6 | 1.4453 | 0.2444 |
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+ | No log | 4.67 | 7 | 1.4082 | 0.2444 |
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+ | No log | 6.0 | 9 | 1.3188 | 0.4222 |
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+ | 1.9051 | 6.67 | 10 | 1.3266 | 0.3556 |
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+ | 1.9051 | 8.0 | 12 | 1.2375 | 0.4667 |
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+ | 1.9051 | 8.67 | 13 | 1.3632 | 0.3778 |
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+ | 1.9051 | 10.0 | 15 | 1.2064 | 0.4 |
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+ | 1.9051 | 10.67 | 16 | 1.5392 | 0.2889 |
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+ | 1.9051 | 12.0 | 18 | 1.1260 | 0.4889 |
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+ | 1.9051 | 12.67 | 19 | 1.0999 | 0.4667 |
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+ | 1.1808 | 14.0 | 21 | 1.2445 | 0.4222 |
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+ | 1.1808 | 14.67 | 22 | 1.2069 | 0.4444 |
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+ | 1.1808 | 16.0 | 24 | 1.0381 | 0.4889 |
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+ | 1.1808 | 16.67 | 25 | 1.0992 | 0.5111 |
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+ | 1.1808 | 18.0 | 27 | 1.1085 | 0.5333 |
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+ | 1.1808 | 18.67 | 28 | 1.0609 | 0.5111 |
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+ | 0.899 | 20.0 | 30 | 1.1754 | 0.5333 |
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+ | 0.899 | 20.67 | 31 | 1.1214 | 0.5333 |
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+ | 0.899 | 22.0 | 33 | 1.2625 | 0.4889 |
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+ | 0.899 | 22.67 | 34 | 1.2586 | 0.5111 |
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+ | 0.899 | 24.0 | 36 | 1.3423 | 0.4667 |
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+ | 0.899 | 24.67 | 37 | 1.4290 | 0.4667 |
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+ | 0.899 | 26.0 | 39 | 1.3722 | 0.5333 |
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+ | 0.4924 | 26.67 | 40 | 1.4024 | 0.5111 |
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+ | 0.4924 | 28.0 | 42 | 1.3396 | 0.5111 |
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+ | 0.4924 | 28.67 | 43 | 1.4100 | 0.4444 |
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+ | 0.4924 | 30.0 | 45 | 1.5561 | 0.4889 |
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+ | 0.4924 | 30.67 | 46 | 1.5223 | 0.5556 |
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+ | 0.4924 | 32.0 | 48 | 1.4581 | 0.5778 |
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+ | 0.4924 | 32.67 | 49 | 1.4627 | 0.5556 |
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+ | 0.1685 | 33.33 | 50 | 1.4814 | 0.5333 |
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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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