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--- |
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library_name: transformers |
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license: other |
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base_model: OpenGVLab/InternVL3-38B-hf |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: sft_captioner |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# sft_captioner |
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This model is a fine-tuned version of [OpenGVLab/InternVL3-38B-hf](https://huggingface.co/OpenGVLab/InternVL3-38B-hf) on the pyq_part1_captioner_0815, the pyq_part2_captioner_0815 and the private_captioner_0815_optimized.json datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7323 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 2025 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.8966 | 0.0868 | 500 | 0.8954 | |
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| 0.861 | 0.1735 | 1000 | 0.8705 | |
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| 0.8622 | 0.2603 | 1500 | 0.8549 | |
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| 0.82 | 0.3470 | 2000 | 0.8349 | |
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| 0.8211 | 0.4338 | 2500 | 0.8202 | |
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| 0.7978 | 0.5206 | 3000 | 0.8064 | |
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| 0.7955 | 0.6073 | 3500 | 0.7945 | |
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| 0.7845 | 0.6941 | 4000 | 0.7838 | |
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| 0.7617 | 0.7808 | 4500 | 0.7729 | |
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| 0.7772 | 0.8676 | 5000 | 0.7622 | |
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| 0.7641 | 0.9544 | 5500 | 0.7544 | |
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| 0.6061 | 1.0411 | 6000 | 0.7635 | |
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| 0.5863 | 1.1279 | 6500 | 0.7613 | |
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| 0.5777 | 1.2146 | 7000 | 0.7588 | |
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| 0.5943 | 1.3014 | 7500 | 0.7490 | |
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| 0.5816 | 1.3882 | 8000 | 0.7469 | |
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| 0.5723 | 1.4749 | 8500 | 0.7421 | |
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| 0.5721 | 1.5617 | 9000 | 0.7374 | |
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| 0.5724 | 1.6484 | 9500 | 0.7353 | |
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| 0.5731 | 1.7352 | 10000 | 0.7343 | |
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| 0.5597 | 1.8220 | 10500 | 0.7330 | |
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| 0.5731 | 1.9087 | 11000 | 0.7326 | |
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| 0.5557 | 1.9955 | 11500 | 0.7323 | |
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### Framework versions |
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- Transformers 4.52.4 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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