base_model, library_name, license, tags, model-index
| base_model | library_name | license | tags | model-index | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | transformers | apache-2.0 |
|
|
tinyllama-1.1b-dpo-pku-saferlhf
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6742
- Rewards/chosen: 0.0508
- Rewards/rejected: 0.0098
- Rewards/accuracies: 0.6750
- Rewards/margins: 0.0410
- Logps/rejected: -205.4332
- Logps/chosen: -232.6254
- Logits/rejected: -2.5959
- Logits/chosen: -2.7163
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_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: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6899 | 0.0960 | 200 | 0.6898 | 0.0058 | -0.0017 | 0.5680 | 0.0074 | -205.5475 | -233.0753 | -2.5954 | -2.7156 |
| 0.6868 | 0.1920 | 400 | 0.6851 | 0.0253 | 0.0080 | 0.6300 | 0.0174 | -205.4510 | -232.8795 | -2.5955 | -2.7157 |
| 0.6741 | 0.2880 | 600 | 0.6806 | 0.0368 | 0.0096 | 0.6410 | 0.0272 | -205.4345 | -232.7647 | -2.5956 | -2.7159 |
| 0.6767 | 0.3840 | 800 | 0.6753 | 0.0499 | 0.0115 | 0.6670 | 0.0384 | -205.4159 | -232.6337 | -2.5954 | -2.7158 |
| 0.676 | 0.4800 | 1000 | 0.6766 | 0.0494 | 0.0133 | 0.6570 | 0.0361 | -205.3982 | -232.6393 | -2.5960 | -2.7163 |
| 0.6774 | 0.5760 | 1200 | 0.6742 | 0.0508 | 0.0098 | 0.6750 | 0.0410 | -205.4332 | -232.6254 | -2.5959 | -2.7163 |
| 0.6746 | 0.6719 | 1400 | 0.6737 | 0.0529 | 0.0107 | 0.6550 | 0.0422 | -205.4236 | -232.6038 | -2.5958 | -2.7162 |
| 0.6678 | 0.7679 | 1600 | 0.6743 | 0.0513 | 0.0104 | 0.6630 | 0.0409 | -205.4272 | -232.6203 | -2.5960 | -2.7164 |
| 0.6833 | 0.8639 | 1800 | 0.6739 | 0.0528 | 0.0108 | 0.6620 | 0.0420 | -205.4227 | -232.6052 | -2.5959 | -2.7163 |
| 0.6743 | 0.9599 | 2000 | 0.6741 | 0.0530 | 0.0115 | 0.6450 | 0.0415 | -205.4160 | -232.6033 | -2.5958 | -2.7163 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.10.0+cu130
- Datasets 2.21.0
- Tokenizers 0.19.1