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---
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base_model: ooliverz/git-large-r-coco-IDB2-V2
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datasets:
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- imagefolder
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library_name: transformers
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: git-large-r-coco-IDB2-V2-IDB_ADv1
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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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# git-large-r-coco-IDB2-V2-IDB_ADv1
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This model is a fine-tuned version of [ooliverz/git-large-r-coco-IDB2-V2](https://huggingface.co/ooliverz/git-large-r-coco-IDB2-V2) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0528
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- Meteor Score: {'meteor': 0.48099544022939256}
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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: 3e-05
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 1024
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- num_epochs: 100
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Meteor Score |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------------------:|
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| 0.0752 | 5.0 | 5 | 0.0707 | {'meteor': 0.45989970933738533} |
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| 0.0562 | 10.0 | 10 | 0.0602 | {'meteor': 0.45979149509400175} |
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| 0.0436 | 15.0 | 15 | 0.0567 | {'meteor': 0.4674583504146179} |
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| 0.0346 | 20.0 | 20 | 0.0530 | {'meteor': 0.4749086336659367} |
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| 0.028 | 25.0 | 25 | 0.0524 | {'meteor': 0.4770807569254236} |
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| 0.0232 | 30.0 | 30 | 0.0512 | {'meteor': 0.4786903333280637} |
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| 0.0196 | 35.0 | 35 | 0.0508 | {'meteor': 0.48157768145979507} |
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| 0.0171 | 40.0 | 40 | 0.0512 | {'meteor': 0.48242689217394297} |
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| 0.0152 | 45.0 | 45 | 0.0515 | {'meteor': 0.48273124613648705} |
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| 0.0139 | 50.0 | 50 | 0.0517 | {'meteor': 0.4813023884740672} |
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| 0.0129 | 55.0 | 55 | 0.0519 | {'meteor': 0.48118479220464483} |
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| 0.0122 | 60.0 | 60 | 0.0521 | {'meteor': 0.48099544022939256} |
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| 0.0115 | 65.0 | 65 | 0.0522 | {'meteor': 0.4803039037483629} |
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| 0.0112 | 70.0 | 70 | 0.0525 | {'meteor': 0.4806395037000483} |
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| 0.0106 | 75.0 | 75 | 0.0527 | {'meteor': 0.48061573437081007} |
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| 0.0105 | 80.0 | 80 | 0.0528 | {'meteor': 0.48061573437081007} |
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| 0.0105 | 85.0 | 85 | 0.0528 | {'meteor': 0.4809716709001543} |
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| 0.0105 | 90.0 | 90 | 0.0528 | {'meteor': 0.4809716709001543} |
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| 0.0103 | 95.0 | 95 | 0.0528 | {'meteor': 0.48099544022939256} |
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| 0.0102 | 100.0 | 100 | 0.0528 | {'meteor': 0.48099544022939256} |
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### Framework versions
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- Transformers 4.46.1
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.20.2
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