lambda-qwen2.5-32b-dpo-test
This model is a fine-tuned version of Qwen/Qwen2.5-32B-Instruct on the tanliboy/orca_dpo_pairs dataset. It achieves the following results on the evaluation set:
- Loss: 0.0003
- Rewards/chosen: -10.1618
- Rewards/rejected: -26.1150
- Rewards/accuracies: 1.0
- Rewards/margins: 15.9532
- Logps/rejected: -3049.5271
- Logps/chosen: -1372.8903
- Logits/rejected: -0.3154
- Logits/chosen: -0.0600
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0103 | 0.2618 | 100 | 0.0060 | -8.5159 | -18.7731 | 1.0 | 10.2572 | -2315.3333 | -1208.2968 | -0.5485 | -0.2481 |
| 0.0005 | 0.5236 | 200 | 0.0005 | -9.9255 | -24.9117 | 1.0 | 14.9862 | -2929.1948 | -1349.2588 | -0.3723 | -0.0661 |
| 0.0005 | 0.7853 | 300 | 0.0004 | -10.0873 | -25.9319 | 1.0 | 15.8446 | -3031.2175 | -1365.4342 | -0.2882 | -0.0014 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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