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---
base_model: meta-llama/Llama-2-7b-hf
library_name: peft
license: llama2
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama-2-7b-hf-DPO-LookAhead-5_TTree1.4_TT0.9_TP0.7_TE0.2_V2
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_V2
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: 1.2147
- Rewards/chosen: -2.3589
- Rewards/rejected: -2.1848
- Rewards/accuracies: 0.3333
- Rewards/margins: -0.1740
- Logps/rejected: -176.9075
- Logps/chosen: -185.7344
- Logits/rejected: -0.3397
- Logits/chosen: -0.3554
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7064 | 0.3020 | 77 | 0.7263 | -0.0650 | -0.0237 | 0.5 | -0.0414 | -155.2957 | -162.7962 | 0.2969 | 0.2895 |
| 0.6816 | 0.6039 | 154 | 0.7127 | -0.1015 | -0.1222 | 0.5 | 0.0207 | -156.2813 | -163.1606 | 0.2989 | 0.2915 |
| 0.6192 | 0.9059 | 231 | 0.7010 | -0.0808 | -0.1624 | 0.5833 | 0.0816 | -156.6835 | -162.9536 | 0.2774 | 0.2692 |
| 0.2805 | 1.2078 | 308 | 0.8302 | -0.5931 | -0.6582 | 0.6667 | 0.0651 | -161.6412 | -168.0767 | 0.1922 | 0.1839 |
| 0.3604 | 1.5098 | 385 | 0.8663 | -0.8552 | -0.8899 | 0.5833 | 0.0347 | -163.9578 | -170.6977 | 0.0866 | 0.0775 |
| 0.3524 | 1.8118 | 462 | 0.9587 | -1.3495 | -1.3440 | 0.5 | -0.0055 | -168.4993 | -175.6406 | -0.0538 | -0.0645 |
| 0.2168 | 2.1137 | 539 | 1.0785 | -1.8309 | -1.7601 | 0.5833 | -0.0708 | -172.6597 | -180.4545 | -0.2246 | -0.2382 |
| 0.0395 | 2.4157 | 616 | 1.2284 | -2.4130 | -2.2406 | 0.3333 | -0.1724 | -177.4654 | -186.2757 | -0.3472 | -0.3633 |
| 0.2081 | 2.7176 | 693 | 1.2147 | -2.3589 | -2.1848 | 0.3333 | -0.1740 | -176.9075 | -185.7344 | -0.3397 | -0.3554 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1 |