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ALFWorld-MPO

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metadata
language:
  - en
license: apache-2.0
library_name: transformers
pipeline_tag: robotics
tags:
  - nlp
  - agent

ALFWorld-MPO

This model is a fine-tuned version of Llama-3.1-8B-Instruct on the alfworld-metaplan-preference-pairs dataset as described in MPO: Boosting LLM Agents with Meta Plan Optimization. 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

File information

The repository contains the following file information:

Filename: tokenizer.json Content: "Content of the file is larger than 50 KB, too long to display."

Filename: all_results.json Content: { "epoch": 3.0, "eval_logits/chosen": -0.33491453528404236, "eval_logits/rejected": -0.3404884338378906, "eval_logps/chosen": -12.90090274810791, "eval_logps/rejected": -19.88900375366211, "eval_loss": 0.8390035629272461, "eval_rewards/accuracies": 0.6317567825317383, "eval_rewards/chosen": -0.5836451649665833, "eval_rewards/margins": 0.680999755859375, "eval_rewards/rejected": -1.2646448612213135, "eval_runtime": 29.3135, "eval_samples_per_second": 10.098, "eval_steps_per_second": 2.524, "total_flos": 11469721436160.0, "train_loss": 0.693384567896525, "train_runtime": 1185.9878, "train_samples_per_second": 6.716, "train_steps_per_second": 0.21 }

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