llama-3-8b-dpo-full
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the trl-lib/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6491
- Rewards/chosen: -0.1814
- Rewards/rejected: -0.2255
- Rewards/accuracies: 0.5625
- Rewards/margins: 0.0441
- Logps/rejected: -419.1795
- Logps/chosen: -335.9990
- Logits/rejected: -1.1373
- Logits/chosen: -1.0280
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: 3e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- total_eval_batch_size: 128
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6411 | 0.8239 | 100 | 0.6494 | -0.1752 | -0.2195 | 0.5625 | 0.0443 | -418.5782 | -335.3811 | -1.1582 | -1.0463 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.20.0
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Model tree for hxssgaa/llama-3-8b-dpo-full
Base model
meta-llama/Meta-Llama-3-8B-Instruct