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_adagrad_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_adagrad_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: 5.9027
+
+## 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: 4
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|
+| 6.708         | 0.77  | 50   | 6.6090          |
+| 6.2622        | 1.54  | 100  | 6.3841          |
+| 6.1083        | 2.31  | 150  | 6.3279          |
+| 6.1302        | 3.08  | 200  | 6.1396          |
+| 6.0668        | 3.85  | 250  | 6.1742          |
+| 5.9788        | 4.62  | 300  | 6.1002          |
+| 5.9065        | 5.38  | 350  | 6.0478          |
+| 5.8597        | 6.15  | 400  | 5.9363          |
+| 5.8188        | 6.92  | 450  | 5.9914          |
+| 5.7599        | 7.69  | 500  | 5.8783          |
+| 5.6732        | 8.46  | 550  | 5.9710          |
+| 5.743         | 9.23  | 600  | 6.0130          |
+| 5.6341        | 10.0  | 650  | 5.8789          |
+| 5.6265        | 10.77 | 700  | 5.8644          |
+| 5.7164        | 11.54 | 750  | 5.9142          |
+| 5.6104        | 12.31 | 800  | 5.9677          |
+| 5.6572        | 13.08 | 850  | 5.8372          |
+| 5.7094        | 13.85 | 900  | 5.8269          |
+| 5.7456        | 14.62 | 950  | 5.9027          |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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