finetune_colpali_v1_2-german-4bit
This model is a fine-tuned version of vidore/colpaligemma-3b-pt-448-base on the German_docx dataset. It achieves the following results on the evaluation set:
- Loss: 0.1100
- Model Preparation Time: 0.008
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch 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: 100
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
---|---|---|---|---|
No log | 0.0533 | 1 | 0.3717 | 0.008 |
1.1358 | 0.5333 | 10 | 0.3356 | 0.008 |
1.2182 | 1.0667 | 20 | 0.2811 | 0.008 |
0.844 | 1.6 | 30 | 0.2365 | 0.008 |
0.7722 | 2.1333 | 40 | 0.1990 | 0.008 |
0.4823 | 2.6667 | 50 | 0.1758 | 0.008 |
0.46 | 3.2 | 60 | 0.1451 | 0.008 |
0.1477 | 3.7333 | 70 | 0.1252 | 0.008 |
0.1764 | 4.2667 | 80 | 0.1258 | 0.008 |
0.2329 | 4.8 | 90 | 0.1100 | 0.008 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.3.1
- Datasets 3.1.0
- Tokenizers 0.20.1
Model tree for svenbl80/finetune_colpali_v1_2-german-4bit
Base model
google/paligemma-3b-pt-448
Finetuned
vidore/colpaligemma-3b-pt-448-base