---
library_name: transformers
license: other
base_model: /home/bl3615/data/Goedel-Prover-SFT
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: dpo_dpo_lean_0_b0.03_f0_lr5e-6_e2
  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. -->

# dpo_dpo_lean_0_b0.03_f0_lr5e-6_e2

This model is a fine-tuned version of [/home/bl3615/data/Goedel-Prover-SFT](https://huggingface.co//home/bl3615/data/Goedel-Prover-SFT) on the dpo_lean_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5357
- Rewards/chosen: -4.1002
- Rewards/rejected: -5.8239
- Rewards/accuracies: 0.7566
- Rewards/margins: 1.7237
- Logps/chosen: -209.7086
- Logps/rejected: -266.5144
- Logits/chosen: -13.4579
- Logits/rejected: -12.9861

## 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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Use 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: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
| 0.5867        | 0.5329 | 500  | 0.5393          | -1.7260        | -2.3840          | 0.7138             | 0.6580          | -130.5684    | -151.8518      | -4.1731       | -3.9948         |
| 0.1708        | 1.0650 | 1000 | 0.5134          | -4.1008        | -5.5590          | 0.7533             | 1.4582          | -209.7289    | -257.6841      | -11.3604      | -10.9174        |
| 0.1112        | 1.5979 | 1500 | 0.5428          | -4.2436        | -5.9501          | 0.7599             | 1.7065          | -214.4901    | -270.7217      | -14.0546      | -13.5623        |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0