Finetuning experiments
Collection
Using common-known datasets to finetune several models. Experiments are run in Colab.
•
6 items
•
Updated
finetuned-Git-base-pokemon-blip-captions-ImageCaptioning
This model is a fine-tuned version of microsoft/git-base on an unknown dataset.
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: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 5
Inference API (serverless) does not yet support transformers models for this pipeline type.
Model tree for JinbiaoZhu/finetuned-Git-base-pokemon-blip-captions-ImageCaptioning
Base model
microsoft/git-base