End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/detr-resnet-101
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+model-index:
+- name: detr-resnet-101_sgd_finetuned_food-roboflow
+  results: []
+---
+
+<!-- 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. -->
+
+# detr-resnet-101_sgd_finetuned_food-roboflow
+
+This model is a fine-tuned version of [facebook/detr-resnet-101](https://huggingface.co/facebook/detr-resnet-101) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.9270
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 6.7367        | 0.77  | 50   | 6.2388          |
+| 5.9103        | 1.54  | 100  | 5.4768          |
+| 4.8918        | 2.31  | 150  | 4.3742          |
+| 3.827         | 3.08  | 200  | 3.8198          |
+| 3.4129        | 3.85  | 250  | 3.3190          |
+| 3.0329        | 4.62  | 300  | 3.1967          |
+| 2.8295        | 5.38  | 350  | 3.1841          |
+| 2.8599        | 6.15  | 400  | 3.1155          |
+| 2.7862        | 6.92  | 450  | 3.1008          |
+| 2.7885        | 7.69  | 500  | 3.0490          |
+| 2.6737        | 8.46  | 550  | 3.0872          |
+| 2.7679        | 9.23  | 600  | 3.0429          |
+| 2.6093        | 10.0  | 650  | 2.9775          |
+| 2.6316        | 10.77 | 700  | 3.0016          |
+| 2.5801        | 11.54 | 750  | 2.9701          |
+| 2.6009        | 12.31 | 800  | 2.8919          |
+| 2.5841        | 13.08 | 850  | 2.9398          |
+| 2.5394        | 13.85 | 900  | 2.9266          |
+| 2.5189        | 14.62 | 950  | 2.9270          |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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