File size: 3,533 Bytes
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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: []
---
<!-- 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. -->
# blip-image-captioning-base-blip2
This model is a fine-tuned version of [Salesforce/blip-image-captioning-base](https://huggingface.co/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
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