|
--- |
|
base_model: google/paligemma-3b-pt-224 |
|
library_name: peft |
|
license: gemma |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: paligemma-cnmc-ft |
|
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-cnmc-ft |
|
|
|
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: 0.1868 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 170 |
|
- num_epochs: 100 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| No log | 0.9645 | 17 | 1.4167 | |
|
| No log | 1.9858 | 35 | 1.1455 | |
|
| 1.2186 | 2.9504 | 52 | 0.6528 | |
|
| 1.2186 | 3.9716 | 70 | 0.3555 | |
|
| 1.2186 | 4.9929 | 88 | 0.2881 | |
|
| 0.3872 | 5.9574 | 105 | 0.2618 | |
|
| 0.3872 | 6.9787 | 123 | 0.2299 | |
|
| 0.3872 | 8.0 | 141 | 0.1961 | |
|
| 0.2563 | 8.9645 | 158 | 0.1834 | |
|
| 0.2563 | 9.9858 | 176 | 0.1523 | |
|
| 0.2563 | 10.9504 | 193 | 0.1612 | |
|
| 0.2196 | 11.9716 | 211 | 0.1505 | |
|
| 0.2196 | 12.9929 | 229 | 0.1868 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.43.0.dev0 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
