End of training

README.md

@@ -1,15 +1,13 @@
 ---
-base_model: vidore/colpaligemma-3b-pt-448-base
-library_name: peft
+library_name: transformers
 license: gemma
+base_model: vidore/colpaligemma-3b-pt-448-base
 tags:
+- colpali
 - generated_from_trainer
-- ColPali
 model-index:
 - name: finetune_colpali_v1_2-ufo-4bit
   results: []
-datasets:
-- davanstrien/ufo-ColPali
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,9 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # finetune_colpali_v1_2-ufo-4bit
 
-This model is a fine-tuned version of [vidore/colpaligemma-3b-pt-448-base](https://huggingface.co/vidore/colpaligemma-3b-pt-448-base) on the [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) dataset.
+This model is a fine-tuned version of [vidore/colpaligemma-3b-pt-448-base](https://huggingface.co/vidore/colpaligemma-3b-pt-448-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1368
+- Loss: 0.1064
+- Model Preparation Time: 0.0056
 
 ## Model description
 
@@ -46,22 +45,22 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 50
-- num_epochs: 2
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 1.5
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| No log        | 0.0041 | 1    | 0.7493          |
-| 0.2096        | 0.8180 | 200  | 0.1816          |
-| 0.0825        | 1.6360 | 400  | 0.1397          |
+| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time |
+|:-------------:|:------:|:----:|:---------------:|:----------------------:|
+| No log        | 0.0041 | 1    | 0.1879          | 0.0056                 |
+| 0.1193        | 0.4090 | 100  | 0.1136          | 0.0056                 |
+| 0.1287        | 0.8180 | 200  | 0.1122          | 0.0056                 |
+| 0.0662        | 1.2270 | 300  | 0.1063          | 0.0056                 |
 
 
 ### Framework versions
 
-- PEFT 0.11.1
 - Transformers 4.44.2
 - Pytorch 2.4.1+cu121
 - Datasets 3.0.0
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1

adapter_model.safetensors

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training_args.bin

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