Model save
Browse files- README.md +64 -0
- config.json +102 -0
- model.safetensors +3 -0
- preprocessor_config.json +36 -0
- runs/May17_08-48-54_umit-ubuntu/events.out.tfevents.1715925001.umit-ubuntu +3 -0
- runs/May18_13-17-14_umit-ubuntu/events.out.tfevents.1716027438.umit-ubuntu +3 -0
- runs/May18_13-29-30_umit-ubuntu/events.out.tfevents.1716028175.umit-ubuntu +3 -0
- runs/May18_13-32-55_umit-ubuntu/events.out.tfevents.1716028376.umit-ubuntu +3 -0
- runs/May18_13-34-21_umit-ubuntu/events.out.tfevents.1716028462.umit-ubuntu +3 -0
- runs/May18_13-35-20_umit-ubuntu/events.out.tfevents.1716028521.umit-ubuntu +3 -0
- runs/May18_13-38-21_umit-ubuntu/events.out.tfevents.1716028702.umit-ubuntu +3 -0
- runs/May18_15-05-00_umit-ubuntu/events.out.tfevents.1716033905.umit-ubuntu +3 -0
- runs/May18_15-05-00_umit-ubuntu/events.out.tfevents.1716034099.umit-ubuntu +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: vit-base-oxford-iiit-pets
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# vit-base-oxford-iiit-pets
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1992
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- Accuracy: 0.9350
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0003
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.3808 | 1.0 | 370 | 0.2939 | 0.9229 |
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| 0.2337 | 2.0 | 740 | 0.2166 | 0.9432 |
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| 0.1762 | 3.0 | 1110 | 0.2010 | 0.9459 |
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| 0.1414 | 4.0 | 1480 | 0.1922 | 0.9513 |
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| 0.136 | 5.0 | 1850 | 0.1895 | 0.9499 |
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### Framework versions
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- Transformers 4.41.0.dev0
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- Pytorch 2.1.2+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "Siamese",
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"1": "Birman",
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"2": "shiba inu",
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"3": "staffordshire bull terrier",
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"4": "basset hound",
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"5": "Bombay",
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"6": "japanese chin",
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"7": "chihuahua",
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"8": "german shorthaired",
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"9": "pomeranian",
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"10": "beagle",
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"11": "english cocker spaniel",
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"12": "american pit bull terrier",
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"13": "Ragdoll",
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"14": "Persian",
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"15": "Egyptian Mau",
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"16": "miniature pinscher",
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"17": "Sphynx",
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"18": "Maine Coon",
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"19": "keeshond",
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"20": "yorkshire terrier",
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"21": "havanese",
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"22": "leonberger",
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"23": "wheaten terrier",
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"24": "american bulldog",
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"25": "english setter",
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"26": "boxer",
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"27": "newfoundland",
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"28": "Bengal",
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"29": "samoyed",
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"30": "British Shorthair",
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"31": "great pyrenees",
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"32": "Abyssinian",
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"33": "pug",
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"34": "saint bernard",
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"35": "Russian Blue",
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"36": "scottish terrier"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Abyssinian": 32,
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"Bengal": 28,
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"Birman": 1,
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"Bombay": 5,
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"British Shorthair": 30,
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"Egyptian Mau": 15,
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"Maine Coon": 18,
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"Persian": 14,
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"Ragdoll": 13,
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"Russian Blue": 35,
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"Siamese": 0,
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"Sphynx": 17,
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"american bulldog": 24,
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"american pit bull terrier": 12,
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"basset hound": 4,
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"beagle": 10,
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"boxer": 26,
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"chihuahua": 7,
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"english cocker spaniel": 11,
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"english setter": 25,
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"german shorthaired": 8,
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"great pyrenees": 31,
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"havanese": 21,
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"japanese chin": 6,
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"keeshond": 19,
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"leonberger": 22,
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"miniature pinscher": 16,
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"newfoundland": 27,
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"pomeranian": 9,
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"pug": 33,
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"saint bernard": 34,
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"samoyed": 29,
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"scottish terrier": 36,
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"shiba inu": 2,
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"staffordshire bull terrier": 3,
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"wheaten terrier": 23,
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"yorkshire terrier": 20
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.41.0.dev0"
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}
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model.safetensors
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preprocessor_config.json
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{
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"_valid_processor_keys": [
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"images",
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"do_resize",
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"size",
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"resample",
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"do_rescale",
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"rescale_factor",
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"do_normalize",
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"image_mean",
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"image_std",
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"return_tensors",
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"data_format",
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"input_data_format"
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],
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTImageProcessor",
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"image_std": [
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0.5,
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 224,
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"width": 224
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}
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}
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runs/May17_08-48-54_umit-ubuntu/events.out.tfevents.1715925001.umit-ubuntu
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runs/May18_13-17-14_umit-ubuntu/events.out.tfevents.1716027438.umit-ubuntu
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runs/May18_13-29-30_umit-ubuntu/events.out.tfevents.1716028175.umit-ubuntu
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