metadata
license: llama3.1
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
model-index:
- name: llama3.1_8b_dpo_bwgenerator_test2
results: []
llama3.1_8b_dpo_bwgenerator_test2
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5181
- Rewards/chosen: -0.4278
- Rewards/rejected: -0.8508
- Rewards/accuracies: 0.9255
- Rewards/margins: 0.4230
- Logps/rejected: -118.6553
- Logps/chosen: -88.8263
- Logits/rejected: -0.9049
- Logits/chosen: -1.6027
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: 2e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6002 | 0.0719 | 1000 | 0.5390 | -0.3845 | -0.7489 | 0.9194 | 0.3644 | -117.6367 | -88.3940 | -0.9017 | -1.6013 |
| 0.5325 | 0.1438 | 2000 | 0.5237 | -0.4184 | -0.8254 | 0.9200 | 0.4070 | -118.4018 | -88.7330 | -0.9052 | -1.6035 |
| 0.5221 | 0.2157 | 3000 | 0.5199 | -0.4201 | -0.8376 | 0.9210 | 0.4175 | -118.5239 | -88.7496 | -0.9038 | -1.6021 |
| 0.518 | 0.2876 | 4000 | 0.5178 | -0.4376 | -0.8621 | 0.9220 | 0.4246 | -118.7688 | -88.9242 | -0.9056 | -1.6036 |
| 0.5177 | 0.3595 | 5000 | 0.5176 | -0.4317 | -0.8563 | 0.9213 | 0.4246 | -118.7104 | -88.8652 | -0.9063 | -1.6039 |
| 0.5186 | 0.4313 | 6000 | 0.5180 | -0.4361 | -0.8604 | 0.9200 | 0.4243 | -118.7512 | -88.9096 | -0.9063 | -1.6040 |
| 0.522 | 0.5032 | 7000 | 0.5175 | -0.4358 | -0.8614 | 0.9210 | 0.4255 | -118.7612 | -88.9070 | -0.9057 | -1.6035 |
| 0.5194 | 0.5751 | 8000 | 0.5182 | -0.4280 | -0.8506 | 0.9249 | 0.4226 | -118.6538 | -88.8285 | -0.9039 | -1.6020 |
| 0.5149 | 0.6470 | 9000 | 0.5179 | -0.4413 | -0.8651 | 0.9229 | 0.4238 | -118.7981 | -88.9612 | -0.9060 | -1.6038 |
| 0.5209 | 0.7189 | 10000 | 0.5178 | -0.4355 | -0.8600 | 0.9216 | 0.4244 | -118.7471 | -88.9040 | -0.9049 | -1.6027 |
| 0.517 | 0.7908 | 11000 | 0.5187 | -0.4343 | -0.8561 | 0.9194 | 0.4217 | -118.7081 | -88.8918 | -0.9046 | -1.6027 |
| 0.5202 | 0.8627 | 12000 | 0.5186 | -0.4321 | -0.8540 | 0.9197 | 0.4220 | -118.6880 | -88.8693 | -0.9047 | -1.6026 |
| 0.5212 | 0.9346 | 13000 | 0.5181 | -0.4278 | -0.8508 | 0.9255 | 0.4230 | -118.6553 | -88.8263 | -0.9049 | -1.6027 |
Framework versions
- PEFT 0.10.0
- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.14.7
- Tokenizers 0.19.1