gemma-7b-dpo-full-mix1-beta-0.05-epoch-3
This model is a fine-tuned version of lewtun/gemma-7b-sft-full-deita-10k-v0 on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:
- Loss: 0.4924
- Rewards/chosen: -3.4915
- Rewards/rejected: -5.2635
- Rewards/accuracies: 0.7396
- Rewards/margins: 1.7720
- Logps/rejected: -556.8203
- Logps/chosen: -523.2347
- Logits/rejected: 83.0993
- Logits/chosen: 88.9292
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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1623 | 1.9 | 100 | 0.4861 | -2.9739 | -4.4977 | 0.6771 | 1.5238 | -541.5043 | -512.8825 | 87.7248 | 93.8502 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1
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Model tree for lewtun/gemma-7b-dpo-full-mix1-beta-0.05-epoch-3
Base model
google/gemma-7b
Finetuned
lewtun/gemma-7b-sft-full-deita-10k-v0