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finetune_colpali_v1_2_fm
seeker317/finetune_colpali_v1_2_fm
finetune_colpali_v1_2_fm is a machine learning model from seeker317. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as gemma.
should probably proofread and complete it, then remove this comment. --
Access
Public
Updated Oct 23, 2024
Repo size
489 MB
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Repo makeup
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.safetensors157 MB · 90%
At a glance
- Library
- transformers
- License
- gemma
- Access
- Public
- Created
- Oct 22, 2024
- Updated
- Oct 23, 2024
- SHA
- d590608e
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
finetune_colpali_v1_2_fm
This model is a fine-tuned version of vidore/colpaligemma-3b-pt-448-base on the fm dataset. It achieves the following results on the evaluation set:
- Loss: 0.1621
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 1 | 0.1707 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.2.0
- Datasets 3.0.2
- Tokenizers 0.20.1
- Library
- transformers
- License
- gemma
- Created
- Oct 22, 2024
- Updated
- Oct 23, 2024