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---
library_name: peft
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama-2-7b-hf-DPO-LookAhead-5_Q2_TTree1.4_TT0.9_TP0.7_TE0.2_V3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Llama-2-7b-hf-DPO-LookAhead-5_Q2_TTree1.4_TT0.9_TP0.7_TE0.2_V3
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8622
- Rewards/chosen: -1.8032
- Rewards/rejected: -1.8934
- Rewards/accuracies: 0.4167
- Rewards/margins: 0.0902
- Logps/rejected: -178.6097
- Logps/chosen: -144.0242
- Logits/rejected: -0.2567
- Logits/chosen: -0.2341
## 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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7186 | 0.3012 | 75 | 0.6922 | 0.0088 | -0.0056 | 0.6667 | 0.0144 | -159.7317 | -125.9045 | 0.2763 | 0.3051 |
| 0.6878 | 0.6024 | 150 | 0.6645 | 0.0065 | -0.0784 | 0.6667 | 0.0850 | -160.4602 | -125.9270 | 0.2430 | 0.2714 |
| 0.7115 | 0.9036 | 225 | 0.6671 | 0.1245 | 0.0380 | 0.5833 | 0.0865 | -159.2964 | -124.7477 | 0.2585 | 0.2872 |
| 0.2588 | 1.2048 | 300 | 0.5773 | -0.4124 | -0.9074 | 0.6667 | 0.4951 | -168.7503 | -130.1161 | 0.1854 | 0.2129 |
| 0.5429 | 1.5060 | 375 | 0.6801 | -0.4887 | -0.7667 | 0.5 | 0.2780 | -167.3426 | -130.8791 | 0.0976 | 0.1239 |
| 0.3313 | 1.8072 | 450 | 0.7539 | -0.6406 | -0.7950 | 0.5 | 0.1545 | -167.6264 | -132.3980 | 0.0143 | 0.0407 |
| 0.2905 | 2.1084 | 525 | 0.8112 | -1.3875 | -1.4781 | 0.4167 | 0.0906 | -174.4566 | -139.8674 | -0.1544 | -0.1306 |
| 0.1737 | 2.4096 | 600 | 0.8469 | -1.9078 | -2.0075 | 0.4167 | 0.0997 | -179.7509 | -145.0706 | -0.2506 | -0.2282 |
| 0.2314 | 2.7108 | 675 | 0.8622 | -1.8032 | -1.8934 | 0.4167 | 0.0902 | -178.6097 | -144.0242 | -0.2567 | -0.2341 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3 |