AA_preference_l0_0_50
This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the AA_preference_l0_0_50 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5682
- Rewards/chosen: 1.6580
- Rewards/rejected: -0.6999
- Rewards/accuracies: 0.7958
- Rewards/margins: 2.3579
- Logps/rejected: -234.7341
- Logps/chosen: -259.9489
- Logits/rejected: -2.1925
- Logits/chosen: -2.2317
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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.5987 | 0.7463 | 50 | 0.6138 | 1.2435 | -0.1587 | 0.7583 | 1.4022 | -229.3223 | -264.0939 | -2.0743 | -2.1097 |
0.2776 | 1.4925 | 100 | 0.5807 | 1.7478 | -0.3381 | 0.75 | 2.0860 | -231.1164 | -259.0504 | -2.1973 | -2.2346 |
0.1711 | 2.2388 | 150 | 0.5595 | 1.4504 | -0.7487 | 0.7833 | 2.1991 | -235.2227 | -262.0249 | -2.1687 | -2.2093 |
0.1884 | 2.9851 | 200 | 0.5684 | 1.6586 | -0.7002 | 0.7917 | 2.3588 | -234.7375 | -259.9425 | -2.1927 | -2.2319 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
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Base model
llava-hf/llava-v1.6-mistral-7b-hf