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---
license: llama2
library_name: peft
tags:
- trl
- orpo
- generated_from_trainer
base_model: meta-llama/Llama-2-7b-hf
model-index:
- name: Llama-2-7b-hf-eval_threapist-ORPO-filtered-version-1
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-eval_threapist-ORPO-filtered-version-1
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: 0.9066
- Rewards/chosen: -0.2061
- Rewards/rejected: -0.2562
- Rewards/accuracies: 0.7000
- Rewards/margins: 0.0500
- Logps/rejected: -2.5615
- Logps/chosen: -2.0611
- Logits/rejected: -1.0229
- Logits/chosen: -1.0111
- Nll Loss: 0.8524
- Log Odds Ratio: -0.5638
- Log Odds Chosen: 0.5622
## 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: 8e-06
- 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: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 0.7757 | 0.4037 | 44 | 1.0979 | -0.2148 | -0.2646 | 0.7000 | 0.0498 | -2.6460 | -2.1485 | -0.9189 | -0.9063 | 1.0343 | -0.5790 | 0.5551 |
| 0.7944 | 0.8073 | 88 | 1.0113 | -0.2113 | -0.2607 | 0.7000 | 0.0494 | -2.6073 | -2.1130 | -0.9711 | -0.9585 | 0.9516 | -0.5747 | 0.5532 |
| 0.6896 | 1.2110 | 132 | 0.9476 | -0.2082 | -0.2579 | 0.7000 | 0.0497 | -2.5794 | -2.0824 | -0.9990 | -0.9867 | 0.8912 | -0.5690 | 0.5574 |
| 0.8565 | 1.6147 | 176 | 0.9066 | -0.2061 | -0.2562 | 0.7000 | 0.0500 | -2.5615 | -2.0611 | -1.0229 | -1.0111 | 0.8524 | -0.5638 | 0.5622 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1 |