llama3_orpo_best_entropy
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the yakazimir/llama3-ultrafeedback-armorm dataset. It achieves the following results on the evaluation set:
- Loss: 2.5561
- Rewards/chosen: -12.9600
- Rewards/rejected: -17.5108
- Rewards/accuracies: 0.8072
- Rewards/margins: 4.5509
- Logps/rejected: -1.7511
- Logps/chosen: -1.2960
- Logits/rejected: -1.3511
- Logits/chosen: -1.3851
- Semantic Entropy: 0.7683
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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Semantic Entropy |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.3262 | 0.8743 | 400 | 2.5608 | -12.8797 | -17.3972 | 0.8072 | 4.5175 | -1.7397 | -1.2880 | -1.3473 | -1.3813 | 0.7719 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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Model tree for yakazimir/llama3_orpo_best_entropy
Base model
meta-llama/Meta-Llama-3-8B-Instruct