|
--- |
|
library_name: peft |
|
license: gemma |
|
base_model: google/paligemma-3b-pt-224 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: paligemma_vqav2_1 |
|
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. --> |
|
|
|
# paligemma_vqav2_1 |
|
|
|
This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4158 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 2 |
|
- num_epochs: 12 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| No log | 0.9976 | 318 | 0.3705 | |
|
| 1.1065 | 1.9984 | 637 | 0.2753 | |
|
| 1.1065 | 2.9992 | 956 | 0.2679 | |
|
| 0.2268 | 4.0 | 1275 | 0.2718 | |
|
| 0.1558 | 4.9976 | 1593 | 0.2638 | |
|
| 0.1558 | 5.9984 | 1912 | 0.2820 | |
|
| 0.1057 | 6.9992 | 2231 | 0.3018 | |
|
| 0.0623 | 8.0 | 2550 | 0.3286 | |
|
| 0.0623 | 8.9976 | 2868 | 0.3621 | |
|
| 0.0325 | 9.9984 | 3187 | 0.3919 | |
|
| 0.0191 | 10.9992 | 3506 | 0.4125 | |
|
| 0.0191 | 11.9718 | 3816 | 0.4158 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.13.2 |
|
- Transformers 4.46.2 |
|
- Pytorch 2.1.2.post304 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.3 |