Nayana-IR-colsmol_v0_1-hi-12k-4bit-LoRA
This model is a fine-tuned version of vidore/ColSmolVLM-base on the Nayana-cognitivelab/Nayana-IR-DescVQA-finetune-hi-47k dataset. It achieves the following results on the evaluation set:
- Loss: 0.1543
- Model Preparation Time: 0.0069
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 OptimizerNames.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 | 0.0013 | 1 | 1.0368 | 0.0069 |
0.3678 | 0.128 | 100 | 0.3771 | 0.0069 |
0.2539 | 0.256 | 200 | 0.2740 | 0.0069 |
0.2645 | 0.384 | 300 | 0.2277 | 0.0069 |
0.1975 | 0.512 | 400 | 0.2020 | 0.0069 |
0.2142 | 0.64 | 500 | 0.1930 | 0.0069 |
0.214 | 0.768 | 600 | 0.1679 | 0.0069 |
0.1734 | 0.896 | 700 | 0.1588 | 0.0069 |
0.1196 | 1.0230 | 800 | 0.1548 | 0.0069 |
0.1263 | 1.1510 | 900 | 0.1546 | 0.0069 |
0.1649 | 1.2790 | 1000 | 0.1486 | 0.0069 |
0.1568 | 1.4070 | 1100 | 0.1545 | 0.0069 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for Nayana-cognitivelab/Nayana-IR-colsmol_v0_1-hi-12k-4bit-LoRA
Base model
HuggingFaceTB/SmolLM2-1.7B
Quantized
HuggingFaceTB/SmolLM2-1.7B-Instruct
Quantized
HuggingFaceTB/SmolVLM-Instruct
Finetuned
vidore/ColSmolVLM-base