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---
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library_name: transformers
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license: mit
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base_model: microsoft/git-large-r-coco
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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model-index:
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- name: git-large-r-coco-IDB_ADv1_COCOv2
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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_COCOv2
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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: 3.0890
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- Meteor Score: {'meteor': 0.4786335839834823}
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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: 32
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- total_train_batch_size: 4096
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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: 150
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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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| 11.2941 | 5.0 | 5 | 9.7802 | {'meteor': 0.047306330587744805} |
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| 9.5485 | 10.0 | 10 | 8.8574 | {'meteor': 0.07078101725961515} |
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| 8.5922 | 15.0 | 15 | 7.9155 | {'meteor': 0.08874535718930834} |
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| 7.8228 | 20.0 | 20 | 7.3148 | {'meteor': 0.12018891275455396} |
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| 7.285 | 25.0 | 25 | 6.8648 | {'meteor': 0.15707348326414072} |
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| 6.8607 | 30.0 | 30 | 6.4858 | {'meteor': 0.19388208635297605} |
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| 6.4959 | 35.0 | 35 | 6.1520 | {'meteor': 0.21120188981070245} |
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| 6.1676 | 40.0 | 40 | 5.8462 | {'meteor': 0.2716218553024612} |
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| 5.8644 | 45.0 | 45 | 5.5574 | {'meteor': 0.3167687928552893} |
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| 5.578 | 50.0 | 50 | 5.2839 | {'meteor': 0.3935488961336244} |
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| 5.3073 | 55.0 | 55 | 5.0231 | {'meteor': 0.4401242744337809} |
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| 5.0514 | 60.0 | 60 | 4.7784 | {'meteor': 0.4548021686867608} |
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| 4.8117 | 65.0 | 65 | 4.5514 | {'meteor': 0.4596569131466085} |
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| 4.5893 | 70.0 | 70 | 4.3420 | {'meteor': 0.45977845518579624} |
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| 4.3842 | 75.0 | 75 | 4.1505 | {'meteor': 0.46392172400764786} |
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| 4.1966 | 80.0 | 80 | 3.9751 | {'meteor': 0.47171195207926336} |
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| 4.0273 | 85.0 | 85 | 3.8188 | {'meteor': 0.47363666995497383} |
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| 3.8755 | 90.0 | 90 | 3.6800 | {'meteor': 0.4762423622409033} |
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| 3.741 | 95.0 | 95 | 3.5578 | {'meteor': 0.4773783003509899} |
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| 3.6242 | 100.0 | 100 | 3.4534 | {'meteor': 0.477309973037375} |
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| 3.5237 | 105.0 | 105 | 3.3645 | {'meteor': 0.4793397639012666} |
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| 3.4397 | 110.0 | 110 | 3.2905 | {'meteor': 0.47738435127434337} |
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| 3.3702 | 115.0 | 115 | 3.2312 | {'meteor': 0.4783368243538133} |
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| 3.3149 | 120.0 | 120 | 3.1840 | {'meteor': 0.47570665785547966} |
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| 3.2715 | 125.0 | 125 | 3.1485 | {'meteor': 0.47646100050859935} |
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| 3.2398 | 130.0 | 130 | 3.1234 | {'meteor': 0.4749786711607146} |
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| 3.2173 | 135.0 | 135 | 3.1059 | {'meteor': 0.4790692343269223} |
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| 3.2025 | 140.0 | 140 | 3.0958 | {'meteor': 0.47859655244912347} |
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| 3.1947 | 145.0 | 145 | 3.0907 | {'meteor': 0.47856080653742605} |
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| 3.1907 | 150.0 | 150 | 3.0890 | {'meteor': 0.4786335839834823} |
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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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