code-extraction / README.md
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---
base_model: google/paligemma-3b-pt-224
datasets:
- imagefolder
library_name: peft
license: gemma
tags:
- generated_from_trainer
model-index:
- name: code-extraction
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. -->
# code-extraction
This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2910
## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1102 | 0.1064 | 10 | 0.9836 |
| 0.9563 | 0.2128 | 20 | 0.8361 |
| 0.8725 | 0.3191 | 30 | 0.7021 |
| 0.8441 | 0.4255 | 40 | 0.5871 |
| 0.6958 | 0.5319 | 50 | 0.5101 |
| 0.6931 | 0.6383 | 60 | 0.4598 |
| 0.5352 | 0.7447 | 70 | 0.4224 |
| 0.4966 | 0.8511 | 80 | 0.3931 |
| 0.6237 | 0.9574 | 90 | 0.3646 |
| 0.4289 | 1.0638 | 100 | 0.3423 |
| 0.5224 | 1.1702 | 110 | 0.3226 |
| 0.5532 | 1.2766 | 120 | 0.3140 |
| 0.3561 | 1.3830 | 130 | 0.3053 |
| 0.3985 | 1.4894 | 140 | 0.3027 |
| 0.39 | 1.5957 | 150 | 0.2992 |
| 0.3741 | 1.7021 | 160 | 0.2943 |
| 0.2028 | 1.8085 | 170 | 0.2898 |
| 0.3935 | 1.9149 | 180 | 0.2910 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1