End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/detr-resnet-50-dc5
+tags:
+- generated_from_trainer
+model-index:
+- name: detr-resnet-50-dc5-fashionpedia-finetuned-jw
+  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-50-dc5-fashionpedia-finetuned-jw
+
+This model is a fine-tuned version of [facebook/detr-resnet-50-dc5](https://huggingface.co/facebook/detr-resnet-50-dc5) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 6.5992
+- eval_map: 0.0
+- eval_map_50: 0.0001
+- eval_map_75: 0.0
+- eval_map_small: 0.0
+- eval_map_medium: 0.0
+- eval_map_large: 0.0002
+- eval_mar_1: 0.0013
+- eval_mar_10: 0.0047
+- eval_mar_100: 0.0059
+- eval_mar_small: 0.0002
+- eval_mar_medium: 0.0051
+- eval_mar_large: 0.0133
+- eval_map_shirt, blouse: 0.0
+- eval_mar_100_shirt, blouse: 0.0
+- eval_map_top, t-shirt, sweatshirt: 0.0
+- eval_mar_100_top, t-shirt, sweatshirt: 0.0
+- eval_map_sweater: 0.0
+- eval_mar_100_sweater: 0.0
+- eval_map_cardigan: 0.0
+- eval_mar_100_cardigan: 0.0
+- eval_map_jacket: 0.0
+- eval_mar_100_jacket: 0.0
+- eval_map_vest: 0.0
+- eval_mar_100_vest: 0.0227
+- eval_map_pants: 0.0
+- eval_mar_100_pants: 0.0
+- eval_map_shorts: 0.0
+- eval_mar_100_shorts: 0.0505
+- eval_map_skirt: 0.0
+- eval_mar_100_skirt: 0.0031
+- eval_map_coat: 0.0
+- eval_mar_100_coat: 0.0
+- eval_map_dress: 0.0013
+- eval_mar_100_dress: 0.0894
+- eval_map_jumpsuit: 0.0
+- eval_mar_100_jumpsuit: 0.0
+- eval_map_cape: 0.0
+- eval_mar_100_cape: 0.02
+- eval_map_glasses: 0.0
+- eval_mar_100_glasses: 0.0
+- eval_map_hat: 0.0
+- eval_mar_100_hat: 0.0
+- eval_map_headband, head covering, hair accessory: 0.0
+- eval_mar_100_headband, head covering, hair accessory: 0.0
+- eval_map_tie: 0.0
+- eval_mar_100_tie: 0.0
+- eval_map_glove: 0.0
+- eval_mar_100_glove: 0.0
+- eval_map_watch: 0.0
+- eval_mar_100_watch: 0.0
+- eval_map_belt: 0.0
+- eval_mar_100_belt: 0.0
+- eval_map_leg warmer: 0.0
+- eval_mar_100_leg warmer: 0.0
+- eval_map_tights, stockings: 0.0
+- eval_mar_100_tights, stockings: 0.0
+- eval_map_sock: 0.0
+- eval_mar_100_sock: 0.0
+- eval_map_shoe: 0.0
+- eval_mar_100_shoe: 0.0
+- eval_map_bag, wallet: 0.0004
+- eval_mar_100_bag, wallet: 0.0453
+- eval_map_scarf: 0.0
+- eval_mar_100_scarf: 0.0
+- eval_map_umbrella: 0.0
+- eval_mar_100_umbrella: 0.0
+- eval_map_hood: 0.0
+- eval_mar_100_hood: 0.0
+- eval_map_collar: 0.0
+- eval_mar_100_collar: 0.0
+- eval_map_lapel: 0.0
+- eval_mar_100_lapel: 0.0
+- eval_map_epaulette: 0.0
+- eval_mar_100_epaulette: 0.0
+- eval_map_sleeve: 0.0001
+- eval_mar_100_sleeve: 0.0213
+- eval_map_pocket: 0.0
+- eval_mar_100_pocket: 0.0
+- eval_map_neckline: 0.0
+- eval_mar_100_neckline: 0.0013
+- eval_map_buckle: 0.0
+- eval_mar_100_buckle: 0.0
+- eval_map_zipper: 0.0
+- eval_mar_100_zipper: 0.0
+- eval_map_applique: 0.0
+- eval_mar_100_applique: 0.0
+- eval_map_bead: 0.0
+- eval_mar_100_bead: 0.0
+- eval_map_bow: 0.0
+- eval_mar_100_bow: 0.0
+- eval_map_flower: 0.0
+- eval_mar_100_flower: 0.0
+- eval_map_fringe: 0.0
+- eval_mar_100_fringe: 0.0167
+- eval_map_ribbon: 0.0
+- eval_mar_100_ribbon: 0.0
+- eval_map_rivet: 0.0
+- eval_mar_100_rivet: 0.0
+- eval_map_ruffle: 0.0
+- eval_mar_100_ruffle: 0.0
+- eval_map_sequin: 0.0
+- eval_mar_100_sequin: 0.0
+- eval_map_tassel: 0.0
+- eval_mar_100_tassel: 0.0
+- eval_runtime: 215.3045
+- eval_samples_per_second: 5.378
+- eval_steps_per_second: 1.347
+- epoch: 0.0044
+- step: 50
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 10000
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.20.1

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