RLAIF-V_Coocur-q0_75
This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the RLAIF-V_Coocur-q0_75 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0131
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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.1348 | 0.2320 | 50 | 1.1268 |
1.08 | 0.4640 | 100 | 1.0813 |
1.0619 | 0.6961 | 150 | 1.0556 |
1.0468 | 0.9281 | 200 | 1.0335 |
0.8999 | 1.1601 | 250 | 1.0276 |
0.8818 | 1.3921 | 300 | 1.0166 |
0.8729 | 1.6241 | 350 | 1.0092 |
0.8653 | 1.8561 | 400 | 1.0026 |
0.7781 | 2.0882 | 450 | 1.0152 |
0.7742 | 2.3202 | 500 | 1.0131 |
0.7689 | 2.5522 | 550 | 1.0138 |
0.7824 | 2.7842 | 600 | 1.0129 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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Model tree for htlou/mm-interp-RLAIF-V_Coocur-q0_75
Base model
llava-hf/llava-v1.6-mistral-7b-hf