File size: 1,346 Bytes
77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 77a7c21 fd557a9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | ---
library_name: peft
license: gemma
base_model: google/codegemma-7b-it
tags:
- base_model:adapter:google/codegemma-7b-it
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: codegemma-7b-securecode
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. -->
# codegemma-7b-securecode
This model is a fine-tuned version of [google/codegemma-7b-it](https://huggingface.co/google/codegemma-7b-it) on the None 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
### Training results
### Framework versions
- PEFT 0.18.1
- Transformers 4.57.6
- Pytorch 2.7.1+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2 |