---
library_name: transformers
base_model: allenai/tulu-2-7b
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- data/tulu-2-7b-uf-rlced-conifer-ref
model-index:
- name: uf-rlced-conifer_tulu-2-7b-group-dpo-no-clip
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# uf-rlced-conifer_tulu-2-7b-group-dpo-no-clip

This model is a fine-tuned version of [allenai/tulu-2-7b](https://huggingface.co/allenai/tulu-2-7b) on the data/tulu-2-7b-uf-rlced-conifer-ref dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6073
- Rewards/chosen: -0.2204
- Rewards/rejected: -0.4189
- Rewards/accuracies: 0.7876
- Rewards/margins: 0.1984
- Logps/rejected: -527.1544
- Logps/chosen: -483.4286
- Logits/rejected: -0.9235
- Logits/chosen: -0.9285

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- 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



### Framework versions

- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1