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ColSmolVLM-Instruct-500M

ColPali
Safetensors
English
idefics3
colsmolvlm
vidore-experimental
vidore
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  1. added_tokens.json +130 -0
  2. chat_template.json +3 -0
  3. config.json +134 -0
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  9. results.json +1 -0
  10. special_tokens_map.json +53 -0
  11. tokenizer.json +0 -0
  12. tokenizer_config.json +1183 -0
  13. training_config.yml +72 -0
  14. vocab.json +0 -0
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training_config.yml ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ config:
2
+ (): colpali_engine.trainer.colmodel_training.ColModelTrainingConfig
3
+ output_dir: !path ../../../models/ColSmolVLM-Instruct-500M
4
+ processor:
5
+ (): colpali_engine.utils.transformers_wrappers.AllPurposeWrapper
6
+ class_to_instanciate: !ext colpali_engine.models.ColIdefics3Processor
7
+ pretrained_model_name_or_path: "./models/ColSmolVLM-Instruct-500M"
8
+ # num_image_tokens: 2048
9
+ # max_length: 50
10
+
11
+ model:
12
+ (): colpali_engine.utils.transformers_wrappers.AllPurposeWrapper
13
+ class_to_instanciate: !ext colpali_engine.models.ColIdefics3
14
+ pretrained_model_name_or_path: "./models/ColSmolVLM-Instruct-500M"
15
+ torch_dtype: !ext torch.bfloat16
16
+ # use_cache: false
17
+ attn_implementation: "flash_attention_2"
18
+ # device_map: "auto"
19
+ # quantization_config:
20
+ # (): transformers.BitsAndBytesConfig
21
+ # load_in_4bit: true
22
+ # bnb_4bit_quant_type: "nf4"
23
+ # bnb_4bit_compute_dtype: "bfloat16"
24
+ # bnb_4bit_use_double_quant: true
25
+
26
+ dataset_loading_func: !ext colpali_engine.utils.dataset_transformation.load_train_set
27
+ eval_dataset_loader: !import ../data/test_data.yaml
28
+
29
+ # max_length: 50
30
+ run_eval: true
31
+ loss_func:
32
+ (): colpali_engine.loss.late_interaction_losses.ColbertPairwiseCELoss
33
+ tr_args:
34
+ (): transformers.training_args.TrainingArguments
35
+ output_dir: null
36
+ overwrite_output_dir: true
37
+ num_train_epochs: 3
38
+ per_device_train_batch_size: 8
39
+ gradient_checkpointing: true
40
+ gradient_checkpointing_kwargs: { "use_reentrant": false }
41
+ # gradient_checkpointing: true
42
+ # 6 x 8 gpus = 48 batch size
43
+ # gradient_accumulation_steps: 4
44
+ per_device_eval_batch_size: 4
45
+ eval_strategy: "steps"
46
+ dataloader_num_workers: 6
47
+ # bf16: true
48
+ save_steps: 500
49
+ logging_steps: 10
50
+ eval_steps: 100
51
+ warmup_steps: 100
52
+ learning_rate: 5e-4
53
+ save_total_limit: 1
54
+ resume_from_checkpoint: true
55
+ # optim: "paged_adamw_8bit"
56
+ # wandb logging
57
+ # wandb_project: "colqwen2"
58
+ # run_name: "colqwen2-ba32-nolora"
59
+ report_to: "wandb"
60
+
61
+
62
+ peft_config:
63
+ (): peft.LoraConfig
64
+ r: 32
65
+ lora_alpha: 32
66
+ lora_dropout: 0.1
67
+ init_lora_weights: "gaussian"
68
+ bias: "none"
69
+ task_type: "FEATURE_EXTRACTION"
70
+ target_modules: '(.*(model.text_model).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$|.*(custom_text_proj).*$)'
71
+ # target_modules: '(.*(language_model).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$|.*(custom_text_proj).*$)'
72
+
vocab.json ADDED
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