llama3-8b-base-dpo-120
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4893
- Rewards/chosen: -0.5883
- Rewards/rejected: -1.3409
- Rewards/accuracies: 0.6905
- Rewards/margins: 0.7525
- Logps/rejected: -293.5897
- Logps/chosen: -331.5697
- Logits/rejected: 0.4485
- Logits/chosen: 0.2338
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-07
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 24
- gradient_accumulation_steps: 5
- total_train_batch_size: 120
- total_eval_batch_size: 48
- 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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.467 | 0.4906 | 250 | 0.4987 | -0.6034 | -1.2547 | 0.7262 | 0.6512 | -291.8655 | -331.8713 | 0.4838 | 0.2542 |
0.4536 | 0.9812 | 500 | 0.4893 | -0.5883 | -1.3409 | 0.6905 | 0.7525 | -293.5897 | -331.5697 | 0.4485 | 0.2338 |
Framework versions
- Transformers 4.42.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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