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_2
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: 0.4486
- Rewards/chosen: -0.1778
- Rewards/rejected: -1.2187
- Rewards/accuracies: 0.8000
- Rewards/margins: 1.0409
- Logps/rejected: -217.7180
- Logps/chosen: -234.9111
- Logits/rejected: -2.4987
- Logits/chosen: -2.6097
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-06
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6075 | 0.0960 | 200 | 0.6052 | 0.4208 | 0.1906 | 0.7170 | 0.2302 | -203.6246 | -228.9246 | -2.5653 | -2.6887 |
| 0.5198 | 0.1920 | 400 | 0.5145 | 0.3083 | -0.2832 | 0.7850 | 0.5915 | -208.3632 | -230.0500 | -2.5310 | -2.6479 |
| 0.4703 | 0.2880 | 600 | 0.4838 | 0.0019 | -0.7989 | 0.7940 | 0.8008 | -213.5201 | -233.1144 | -2.5215 | -2.6339 |
| 0.5223 | 0.3840 | 800 | 0.4631 | 0.1561 | -0.7414 | 0.7880 | 0.8975 | -212.9448 | -231.5717 | -2.4968 | -2.6118 |
| 0.4335 | 0.4800 | 1000 | 0.4555 | -0.1607 | -1.1551 | 0.7950 | 0.9944 | -217.0816 | -234.7399 | -2.4976 | -2.6097 |
| 0.5214 | 0.5760 | 1200 | 0.4511 | -0.1319 | -1.1471 | 0.7990 | 1.0152 | -217.0018 | -234.4519 | -2.5001 | -2.6120 |
| 0.4784 | 0.6719 | 1400 | 0.4486 | -0.1778 | -1.2187 | 0.8000 | 1.0409 | -217.7180 | -234.9111 | -2.4987 | -2.6097 |
| 0.4223 | 0.7679 | 1600 | 0.4487 | -0.1274 | -1.1676 | 0.7990 | 1.0402 | -217.2067 | -234.4066 | -2.4987 | -2.6100 |
| 0.5114 | 0.8639 | 1800 | 0.4483 | -0.1119 | -1.1535 | 0.7990 | 1.0416 | -217.0661 | -234.2521 | -2.4988 | -2.6100 |
| 0.4763 | 0.9599 | 2000 | 0.4485 | -0.1144 | -1.1552 | 0.7950 | 1.0409 | -217.0830 | -234.2766 | -2.4989 | -2.6102 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.10.0+cu130
- Datasets 2.21.0
- Tokenizers 0.19.1