Model save

README.md

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 ---
-{}
+library_name: transformers
+license: apache-2.0
+base_model: liaujianjie/detr-resnet-50
+tags:
+- generated_from_trainer
+model-index:
+- name: detr-group37-liaujianjie-resnet-50
+  results: []
 ---
 
-    ## DETR for Traffic Analysis - detr-group37-liaujianjie-resnet-50
-
-    ## Model Description
-    This model is a fine-tuned version of [liaujianjie/detr-resnet-50] for detecting vehicles in traffic camera images. The model was trained for improved vehicle detection in traffic scenarios.
-
-    ## Training Data
-    The model was trained on the [slliac/isom5240-td-traffic-analysis], which contains traffic camera images with annotations for various vehicle types.
-    ## Training Details
-    - **Base Model**: liaujianjie/detr-resnet-50
-    - **Training Dataset Size**: 786 examples
-    - **Epochs**: 2
-    - **Batch Size**: 2
-    - **Learning Rate**: 5e-05
-    - **Weight Decay**: 1e-4
-    - **Training Date**: 2025-03-26
-    - **Final Training Loss**: 1.3216
-    - **Training Time**: 152.35 seconds
-
-    ## Performance Metrics
-    - **Training Loss**: 1.3216
-    - **Samples per Second**: 10.32
-    - **Steps per Second**: 5.16 
+<!-- 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-group37-liaujianjie-resnet-50
+
+This model is a fine-tuned version of [liaujianjie/detr-resnet-50](https://huggingface.co/liaujianjie/detr-resnet-50) on an unknown dataset.
+
+## 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: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.50.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1

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