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---
library_name: transformers
license: llama3.1
base_model: mlfoundations-dev/stackexchange_christianity
tags:
- llama-factory
- full
- trl
- dpo
- llama-factory
- generated_from_trainer
model-index:
- name: simpo-stackexchange_christianity
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. -->
# simpo-stackexchange_christianity
This model is a fine-tuned version of [mlfoundations-dev/stackexchange_christianity](https://huggingface.co/mlfoundations-dev/stackexchange_christianity) on the mlfoundations-dev/gemma2-ultrafeedback-armorm dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5820
- Rewards/chosen: -43.5673
- Rewards/rejected: -50.3578
- Rewards/accuracies: 0.7914
- Rewards/margins: 6.7905
- Logps/chosen: -4.3567
- Logps/rejected: -5.0358
- Logits/chosen: -0.9251
- Logits/rejected: -0.9405
## 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-07
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
| 2.7111 | 0.9997 | 442 | 2.5820 | -43.5673 | -50.3578 | 0.7914 | 6.7905 | -4.3567 | -5.0358 | -0.9251 | -0.9405 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3