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---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- trl
- dpo
- generated_from_trainer
library_name: peft
model-index:
- name: Llama-2-7b-hf-DPO-LookAhead-0_TTree1.4_TT0.9_TP0.7_TE0.2_V6
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-0_TTree1.4_TT0.9_TP0.7_TE0.2_V6
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: 0.9591
- Rewards/chosen: -2.8498
- Rewards/rejected: -3.2567
- Rewards/accuracies: 0.6000
- Rewards/margins: 0.4069
- Logps/rejected: -145.1960
- Logps/chosen: -111.9480
- Logits/rejected: 0.1780
- Logits/chosen: 0.1994
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6832 | 0.3007 | 69 | 0.6916 | -0.1597 | -0.1889 | 0.4000 | 0.0292 | -114.5179 | -85.0475 | 0.6233 | 0.6414 |
| 0.7529 | 0.6013 | 138 | 0.6560 | -0.2047 | -0.3472 | 0.5 | 0.1425 | -116.1010 | -85.4976 | 0.6177 | 0.6354 |
| 0.693 | 0.9020 | 207 | 0.6636 | 0.0291 | -0.0598 | 0.5 | 0.0889 | -113.2271 | -83.1593 | 0.6143 | 0.6331 |
| 0.4049 | 1.2026 | 276 | 0.6820 | -0.9628 | -1.4793 | 0.5 | 0.5166 | -127.4224 | -93.0781 | 0.5148 | 0.5312 |
| 0.3698 | 1.5033 | 345 | 0.6524 | -1.3282 | -1.9360 | 0.6000 | 0.6078 | -131.9892 | -96.7321 | 0.4151 | 0.4326 |
| 0.3176 | 1.8039 | 414 | 0.7491 | -1.8527 | -2.3707 | 0.6000 | 0.5180 | -136.3361 | -101.9771 | 0.3469 | 0.3652 |
| 0.361 | 2.1046 | 483 | 0.8110 | -2.2972 | -2.7632 | 0.5 | 0.4660 | -140.2609 | -106.4225 | 0.2734 | 0.2932 |
| 0.3286 | 2.4052 | 552 | 0.9465 | -2.7604 | -3.1816 | 0.6000 | 0.4212 | -144.4454 | -111.0542 | 0.1886 | 0.2099 |
| 0.0545 | 2.7059 | 621 | 0.9591 | -2.8498 | -3.2567 | 0.6000 | 0.4069 | -145.1960 | -111.9480 | 0.1780 | 0.1994 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1 |