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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_TTree1.4_TT0.9_TP0.7_TE0.2_V7
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_TTree1.4_TT0.9_TP0.7_TE0.2_V7
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: 0.7581
- Rewards/chosen: -1.7006
- Rewards/rejected: -1.8759
- Rewards/accuracies: 0.6000
- Rewards/margins: 0.1753
- Logps/rejected: -131.1391
- Logps/chosen: -96.3973
- Logits/rejected: -0.0046
- Logits/chosen: 0.0503
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7096 | 0.3004 | 67 | 0.6970 | -0.0217 | -0.0183 | 0.5 | -0.0034 | -112.5630 | -79.6082 | 0.6024 | 0.6487 |
| 0.6684 | 0.6009 | 134 | 0.6829 | -0.0429 | -0.0704 | 0.8000 | 0.0275 | -113.0842 | -79.8203 | 0.5780 | 0.6246 |
| 0.7283 | 0.9013 | 201 | 0.6982 | 0.0550 | 0.0616 | 0.6000 | -0.0067 | -111.7634 | -78.8413 | 0.5848 | 0.6319 |
| 0.2339 | 1.2018 | 268 | 0.6630 | -0.1631 | -0.2504 | 0.7000 | 0.0873 | -114.8840 | -81.0225 | 0.4681 | 0.5163 |
| 0.3526 | 1.5022 | 335 | 0.6523 | -0.5545 | -0.6837 | 0.6000 | 0.1292 | -119.2165 | -84.9362 | 0.3518 | 0.4006 |
| 0.2787 | 1.8027 | 402 | 0.6181 | -0.4772 | -0.6749 | 0.6000 | 0.1977 | -119.1291 | -84.1633 | 0.3107 | 0.3615 |
| 0.2577 | 2.1031 | 469 | 0.6856 | -1.0419 | -1.1941 | 0.5 | 0.1522 | -124.3209 | -89.8106 | 0.1666 | 0.2190 |
| 0.0942 | 2.4036 | 536 | 0.7344 | -1.5330 | -1.7182 | 0.6000 | 0.1852 | -129.5615 | -94.7212 | 0.0278 | 0.0822 |
| 0.0952 | 2.7040 | 603 | 0.7581 | -1.7006 | -1.8759 | 0.6000 | 0.1753 | -131.1391 | -96.3973 | -0.0046 | 0.0503 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3 |