| language: | |
| - en | |
| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: text-generation | |
| tags: | |
| - nlp | |
| - agent | |
| # ALFWorld-MPO | |
| This model is a fine-tuned version of Llama-3.1-8B-Instruct on the [alfworld-metaplan-preference-pairs](https://huggingface.co/datasets/xwm/Meta_Plan_Optimization/blob/main/alfworld_metaplan_preference_pairs.json) dataset as described in [MPO: Boosting LLM Agents with Meta Plan Optimization](https://hf.co/papers/2503.02682). | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.8390 | |
| - Rewards/chosen: -0.5836 | |
| - Rewards/rejected: -1.2646 | |
| - Rewards/accuracies: 0.6318 | |
| - Rewards/margins: 0.6810 | |
| - Logps/chosen: -12.9009 | |
| - Logps/rejected: -19.8890 | |
| - Logits/chosen: -0.3349 | |
| - Logits/rejected: -0.3405 | |
| ## 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: 1e-05 | |
| - train_batch_size: 2 | |
| - eval_batch_size: 1 | |
| - seed: 42 | |
| - distributed_type: multi-GPU | |
| - num_devices: 4 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 32 | |
| - total_eval_batch_size: 4 | |
| - 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: 0.03 | |
| - num_epochs: 3.0 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.46.1 | |
| - Pytorch 2.5.1+cu124 | |
| - Datasets 3.1.0 | |
| - Tokenizers 0.20.3 | |
| ## Code | |
| [https://github.com/WeiminXiong/MPO](https://github.com/WeiminXiong/MPO) |