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---
license: llama2
base_model: elichen3051/llama2-7b-sft-chat-no-template
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama2-7b-sft-chat-no-template-dpo
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. -->
# llama2-7b-sft-chat-no-template-dpo
This model is a fine-tuned version of [elichen3051/llama2-7b-sft-chat-no-template](https://huggingface.co/elichen3051/llama2-7b-sft-chat-no-template) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6026
- Rewards/chosen: -0.9396
- Rewards/rejected: -1.3040
- Rewards/accuracies: 0.6560
- Rewards/margins: 0.3644
- Logps/rejected: -372.5772
- Logps/chosen: -371.2111
- Logits/rejected: -1.0199
- Logits/chosen: -1.0320
## 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-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5619 | 0.9987 | 477 | 0.6026 | -0.9396 | -1.3040 | 0.6560 | 0.3644 | -372.5772 | -371.2111 | -1.0199 | -1.0320 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.2
- Tokenizers 0.19.1
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