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--- |
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library_name: transformers |
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license: other |
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base_model: llava-hf/llava-v1.6-mistral-7b-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: RLAIF-V-Dataset |
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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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# RLAIF-V-Dataset |
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This model is a fine-tuned version of [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) on the RLAIF-V-Dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4467 |
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- Rewards/chosen: -3.1988 |
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- Rewards/rejected: -5.9606 |
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- Rewards/accuracies: 0.8163 |
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- Rewards/margins: 2.7618 |
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- Logps/rejected: -218.4866 |
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- Logps/chosen: -190.4653 |
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- Logits/rejected: -2.3732 |
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- Logits/chosen: -2.4055 |
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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-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.5777 | 0.1709 | 50 | 0.5813 | -0.4541 | -1.0668 | 0.6683 | 0.6127 | -169.5483 | -163.0182 | -2.5153 | -2.5221 | |
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| 0.4982 | 0.3419 | 100 | 0.5161 | -0.9806 | -2.1974 | 0.7212 | 1.2168 | -180.8539 | -168.2832 | -2.4606 | -2.4847 | |
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| 0.4954 | 0.5128 | 150 | 0.4770 | -1.5352 | -3.2803 | 0.7548 | 1.7451 | -191.6833 | -173.8291 | -2.0991 | -2.1473 | |
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| 0.4567 | 0.6838 | 200 | 0.4598 | -1.1951 | -2.8406 | 0.7596 | 1.6455 | -187.2865 | -170.4288 | -2.1090 | -2.1587 | |
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| 0.4873 | 0.8547 | 250 | 0.4487 | -1.9205 | -3.6640 | 0.7635 | 1.7435 | -195.5203 | -177.6819 | -2.5457 | -2.5724 | |
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| 0.2176 | 1.0256 | 300 | 0.4383 | -1.1991 | -3.1202 | 0.7846 | 1.9211 | -190.0823 | -170.4688 | -2.3130 | -2.3490 | |
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| 0.2095 | 1.1966 | 350 | 0.4537 | -2.3545 | -4.8732 | 0.7933 | 2.5188 | -207.6123 | -182.0219 | -2.3656 | -2.3942 | |
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| 0.1952 | 1.3675 | 400 | 0.4353 | -1.9722 | -4.1870 | 0.7962 | 2.2148 | -200.7505 | -178.1995 | -2.3058 | -2.3361 | |
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| 0.1819 | 1.5385 | 450 | 0.4321 | -2.0466 | -4.4416 | 0.8077 | 2.3950 | -203.2960 | -178.9431 | -2.2282 | -2.2612 | |
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| 0.1932 | 1.7094 | 500 | 0.4247 | -1.8597 | -4.1324 | 0.8087 | 2.2727 | -200.2041 | -177.0739 | -2.2659 | -2.2970 | |
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| 0.1921 | 1.8803 | 550 | 0.4131 | -2.3219 | -4.8505 | 0.8183 | 2.5286 | -207.3855 | -181.6965 | -2.3691 | -2.3985 | |
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| 0.0868 | 2.0513 | 600 | 0.4392 | -2.7792 | -5.2414 | 0.8135 | 2.4623 | -211.2946 | -186.2690 | -2.4330 | -2.4615 | |
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| 0.0825 | 2.2222 | 650 | 0.4447 | -3.2209 | -6.0852 | 0.8154 | 2.8642 | -219.7319 | -190.6867 | -2.3962 | -2.4295 | |
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| 0.0925 | 2.3932 | 700 | 0.4449 | -3.2092 | -6.0685 | 0.8183 | 2.8593 | -219.5651 | -190.5695 | -2.3854 | -2.4189 | |
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| 0.0754 | 2.5641 | 750 | 0.4567 | -3.3570 | -6.0710 | 0.8115 | 2.7141 | -219.5908 | -192.0472 | -2.3789 | -2.4105 | |
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| 0.0707 | 2.7350 | 800 | 0.4484 | -3.2447 | -6.0070 | 0.8135 | 2.7622 | -218.9498 | -190.9248 | -2.3739 | -2.4066 | |
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| 0.0739 | 2.9060 | 850 | 0.4468 | -3.2032 | -5.9670 | 0.8173 | 2.7638 | -218.5504 | -190.5096 | -2.3732 | -2.4054 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.3 |
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