YAML Metadata
Warning:
The pipeline tag "visual-document-retrieval" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, any-to-any, other
finetune_colpali_v1_2-vdsid_french-4bit
This model is a fine-tuned version of vidore/colpaligemma-3b-pt-448-base on the vidore/vdsid_french dataset. It achieves the following results on the evaluation set:
- Loss: 0.0212
- Model Preparation Time: 0.0144
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: 1.5
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|---|---|---|---|---|
| No log | 0.0034 | 1 | 0.0571 | 0.0144 |
| 0.0397 | 0.3404 | 100 | 0.0247 | 0.0144 |
| 0.0195 | 0.6809 | 200 | 0.0266 | 0.0144 |
| 0.0098 | 1.0213 | 300 | 0.0240 | 0.0144 |
| 0.0299 | 1.3617 | 400 | 0.0223 | 0.0144 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.20.1
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The HF Inference API does not support visual-document-retrieval models for transformers library.
Model tree for pontino/finetune_colpali_v1_2-vdsid_french-4bit
Base model
google/paligemma-3b-pt-448
Finetuned
vidore/colpaligemma-3b-pt-448-base