IndoColSmol-500M
This model is a fine-tuned version of vidore/ColSmolVLM-Instruct-500M-base on the ingenio/indodvqa_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.3641
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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_ratio: 0.1
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0099 | 1 | 0.4474 |
0.4523 | 0.3960 | 40 | 0.4055 |
0.3996 | 0.7921 | 80 | 0.3804 |
0.3637 | 1.1881 | 120 | 0.3687 |
0.345 | 1.5842 | 160 | 0.3627 |
0.3466 | 1.9802 | 200 | 0.3630 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1
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Model tree for ingenio/IndoColSmol-500M
Base model
HuggingFaceTB/SmolLM2-360M
Quantized
HuggingFaceTB/SmolLM2-360M-Instruct
Quantized
HuggingFaceTB/SmolVLM-500M-Instruct
Finetuned
vidore/ColSmolVLM-Instruct-500M-base