Image Classification
Transformers
PyTorch
TensorBoard
resnet
Generated from Trainer
Eval Results (legacy)
Instructions to use Soulaimen/resnet-50-bottomCleanedData with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Soulaimen/resnet-50-bottomCleanedData with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Soulaimen/resnet-50-bottomCleanedData") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Soulaimen/resnet-50-bottomCleanedData") model = AutoModelForImageClassification.from_pretrained("Soulaimen/resnet-50-bottomCleanedData") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
all_results.json
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"eval_runtime": 7.5653,
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"eval_steps_per_second": 14.672,
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"total_flos": 8.379994919518495e+18,
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"train_loss": 0.43237863398612814,
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"train_runtime": 6732.481,
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"train_steps_per_second": 1.047
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eval_results.json
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"epoch": 49.8,
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"eval_accuracy": 0.9761634506242906,
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"eval_loss": 0.08218241482973099,
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"eval_runtime": 7.5653,
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"eval_samples_per_second": 116.453,
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"eval_steps_per_second": 14.672
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runs/May06_20-15-33_cfa7f4cd76a3/events.out.tfevents.1683410906.cfa7f4cd76a3.950.5
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version https://git-lfs.github.com/spec/v1
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size 411
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train_results.json
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"epoch": 49.8,
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"total_flos": 8.379994919518495e+18,
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"train_loss": 0.43237863398612814,
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"train_runtime": 6732.481,
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"train_samples_per_second": 58.842,
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trainer_state.json
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