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---
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base_model: microsoft/git-large-r-coco
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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-IDB_ADv1_COCOv6-rv2
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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-IDB_ADv1_COCOv6-rv2
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This model is a fine-tuned version of [microsoft/git-large-r-coco](https://huggingface.co/microsoft/git-large-r-coco) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0934
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- Meteor Score: {'meteor': 0.6849337864778346}
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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: 6
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 96
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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_with_restarts
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- lr_scheduler_warmup_steps: 50
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- num_epochs: 20
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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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| 0.7802 | 5.0 | 5 | 0.1019 | {'meteor': 0.6667354024231188} |
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| 0.756 | 10.0 | 10 | 0.1006 | {'meteor': 0.6766394690979587} |
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| 0.7057 | 15.0 | 15 | 0.0972 | {'meteor': 0.6774630113691023} |
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| 0.6349 | 20.0 | 20 | 0.0934 | {'meteor': 0.6849337864778346} |
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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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