readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - coco_dataset_script
  metrics:
  - rouge
  model-index:
  - name: ImageCaptioner
    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. -->
  
  # ImageCaptioner
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the coco_dataset_script dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3321
  - Rouge1: 20.6921
  - Rouge2: 3.9793
  - Rougel: 19.3721
  - Rougelsum: 19.3726
  - Gen Len: 14.875
  
  ## 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: 5e-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
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 20   | 0.3409          | 18.174  | 0.5969 | 18.2232 | 18.2879   | 7.0     |
  | No log        | 2.0   | 40   | 0.3334          | 19.8058 | 2.7069 | 18.3788 | 18.3121   | 13.375  |
  | No log        | 3.0   | 60   | 0.3321          | 20.6921 | 3.9793 | 19.3721 | 19.3726   | 14.875  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  