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metadata
library_name: transformers
license: bsd-3-clause
base_model: Salesforce/blip-image-captioning-base
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: blip-image-captioning-base-blip2
    results: []

blip-image-captioning-base-blip2

This model is a fine-tuned version of Salesforce/blip-image-captioning-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4501
  • Wer: 0.8353

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.1988 1.576 50 0.3600 0.8457
0.2346 3.128 100 0.3105 0.8388
0.1382 4.704 150 0.3111 0.8431
0.0779 6.256 200 0.3312 0.8388
0.0429 7.832 250 0.3430 0.8397
0.0248 9.384 300 0.3507 0.8448
0.0169 10.96 350 0.3602 0.8267
0.0113 12.512 400 0.3684 0.8448
0.0087 14.064 450 0.3737 0.8414
0.0059 15.64 500 0.3814 0.8422
0.0049 17.192 550 0.3762 0.8284
0.0036 18.768 600 0.3785 0.8388
0.0026 20.32 650 0.3805 0.8422
0.0023 21.896 700 0.3892 0.8414
0.0019 23.448 750 0.3901 0.8414
0.0016 25.0 800 0.3903 0.8371
0.0012 26.576 850 0.3999 0.8431
0.0009 28.128 900 0.4078 0.8457
0.0008 29.704 950 0.4049 0.8414
0.0008 31.256 1000 0.4063 0.8345
0.0005 32.832 1050 0.4133 0.8362
0.0004 34.384 1100 0.4173 0.8353
0.0003 35.96 1150 0.4238 0.8405
0.0003 37.512 1200 0.4254 0.8388
0.0002 39.064 1250 0.4263 0.8293
0.0001 40.64 1300 0.4326 0.8293
0.0001 42.192 1350 0.4376 0.8371
0.0001 43.768 1400 0.4391 0.8302
0.0 45.32 1450 0.4450 0.8388
0.0001 46.896 1500 0.4464 0.8328
0.0 48.448 1550 0.4488 0.8353
0.0 50.0 1600 0.4501 0.8353

Framework versions

  • Transformers 4.52.4
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.2