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---
license: llama2
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: meta-llama/Llama-2-7b-chat-hf
model-index:
- name: model_hh_usp2_200
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. -->
# model_hh_usp2_200
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7539
- Rewards/chosen: -6.1342
- Rewards/rejected: -7.0734
- Rewards/accuracies: 0.5500
- Rewards/margins: 0.9392
- Logps/rejected: -123.0264
- Logps/chosen: -118.7056
- Logits/rejected: -0.0859
- Logits/chosen: -0.0281
## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0 | 8.0 | 100 | 1.7627 | -5.8776 | -6.7947 | 0.5400 | 0.9171 | -122.7167 | -118.4203 | -0.0739 | -0.0163 |
| 0.0 | 16.0 | 200 | 1.7526 | -5.9719 | -6.9070 | 0.5200 | 0.9351 | -122.8416 | -118.5252 | -0.0772 | -0.0191 |
| 0.0 | 24.0 | 300 | 1.7452 | -5.9893 | -6.9334 | 0.5400 | 0.9440 | -122.8708 | -118.5445 | -0.0823 | -0.0239 |
| 0.0 | 32.0 | 400 | 1.7405 | -6.0454 | -7.0112 | 0.5400 | 0.9658 | -122.9573 | -118.6068 | -0.0827 | -0.0247 |
| 0.0 | 40.0 | 500 | 1.7542 | -6.0927 | -7.0508 | 0.5500 | 0.9581 | -123.0013 | -118.6594 | -0.0849 | -0.0269 |
| 0.0 | 48.0 | 600 | 1.7457 | -6.1288 | -7.0751 | 0.5300 | 0.9463 | -123.0282 | -118.6995 | -0.0843 | -0.0262 |
| 0.0 | 56.0 | 700 | 1.7426 | -6.1364 | -7.0982 | 0.5400 | 0.9619 | -123.0540 | -118.7079 | -0.0868 | -0.0288 |
| 0.0 | 64.0 | 800 | 1.7365 | -6.1361 | -7.0983 | 0.5600 | 0.9621 | -123.0540 | -118.7077 | -0.0867 | -0.0287 |
| 0.0 | 72.0 | 900 | 1.7559 | -6.1205 | -7.0808 | 0.5500 | 0.9604 | -123.0346 | -118.6903 | -0.0874 | -0.0288 |
| 0.0 | 80.0 | 1000 | 1.7539 | -6.1342 | -7.0734 | 0.5500 | 0.9392 | -123.0264 | -118.7056 | -0.0859 | -0.0281 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |