sablo-pebble-mistral-dpo-lora-HelpSteer_binarized-2
This model is a fine-tuned version of sablo/sablo-pebble-mistral on the sablo/HelpSteer_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5195
- Rewards/chosen: -1.3821
- Rewards/rejected: -2.4510
- Rewards/accuracies: 0.7358
- Rewards/margins: 1.0689
- Logps/rejected: -158.5470
- Logps/chosen: -147.7195
- Logits/rejected: -2.0952
- Logits/chosen: -2.1922
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: 5e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.65 | 0.2 | 200 | 0.6563 | 0.1070 | 0.0177 | 0.6509 | 0.0893 | -76.2561 | -98.0835 | -2.0464 | -2.1421 |
0.456 | 0.39 | 400 | 0.5446 | -1.2305 | -1.8748 | 0.7217 | 0.6444 | -139.3410 | -142.6661 | -2.1203 | -2.2102 |
0.4388 | 0.59 | 600 | 0.5325 | -1.8012 | -2.8927 | 0.7123 | 1.0915 | -173.2708 | -161.6904 | -2.1017 | -2.1954 |
0.6137 | 0.79 | 800 | 0.5198 | -1.4487 | -2.5199 | 0.7382 | 1.0712 | -160.8413 | -149.9388 | -2.0962 | -2.1935 |
0.5866 | 0.98 | 1000 | 0.5195 | -1.3821 | -2.4510 | 0.7358 | 1.0689 | -158.5470 | -147.7195 | -2.0952 | -2.1922 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.15.0
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Model tree for dctanner/sablo-pebble-mistral-dpo-lora-HelpSteer_binarized-2
Base model
sablo/sablo-pebble-mistral