zephyr-7b-gemma-dpo
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-gemma-sft-v0.1 on the RedaAlami/PKU-SafeRLHF-Processed dataset. It achieves the following results on the evaluation set:
- Loss: 97.2382
- Rewards/chosen: 0.0424
- Rewards/rejected: 0.0341
- Rewards/accuracies: 0.6062
- Rewards/margins: 0.0083
- Logps/rejected: -2.3880
- Logps/chosen: -2.3290
- Logits/rejected: 384.5392
- Logits/chosen: 412.5483
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: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
99.2543 | 0.3017 | 100 | 98.5109 | 0.0407 | 0.0354 | 0.5822 | 0.0053 | -2.3624 | -2.3625 | 390.8526 | 418.0560 |
98.8709 | 0.6033 | 200 | 98.0235 | 0.0431 | 0.0367 | 0.5788 | 0.0063 | -2.3359 | -2.3153 | 388.3781 | 415.9555 |
97.9389 | 0.9050 | 300 | 97.6159 | 0.0460 | 0.0381 | 0.5959 | 0.0078 | -2.3082 | -2.2581 | 386.4085 | 414.2633 |
96.4776 | 1.2066 | 400 | 97.3138 | 0.0431 | 0.0347 | 0.5908 | 0.0083 | -2.3763 | -2.3158 | 385.0537 | 413.0242 |
97.3613 | 1.5083 | 500 | 97.2518 | 0.0430 | 0.0346 | 0.5908 | 0.0083 | -2.3781 | -2.3180 | 384.5959 | 412.6117 |
97.5077 | 1.8100 | 600 | 97.2543 | 0.0424 | 0.0341 | 0.5976 | 0.0083 | -2.3888 | -2.3300 | 384.5274 | 412.5387 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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