dpo4
This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 18.2999
- Rewards/chosen: -55.1127
- Rewards/rejected: -55.1897
- Rewards/accuracies: 0.4073
- Rewards/margins: 0.0770
- Logps/rejected: -625.9051
- Logps/chosen: -588.4946
- Logits/rejected: -8.9525
- Logits/chosen: -8.9519
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: 0.1
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 4
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22.9478 | 2.3088 | 100 | 18.2999 | -55.1127 | -55.1897 | 0.4073 | 0.0770 | -625.9051 | -588.4946 | -8.9525 | -8.9519 |
Framework versions
- PEFT 0.10.0
- Transformers 4.45.0
- Pytorch 2.5.1+cu124
- Datasets 2.19.2
- Tokenizers 0.20.3
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Base model
deepseek-ai/deepseek-coder-1.3b-base