Yuan-Li-FNLP/R3-RAG-CS-Qwen

Model

should probably proofread and complete it, then remove this comment. -->

1

2 commits

1 linked in READMEs

updated May 26, 2025

See the code

README

qwen

This model is a fine-tuned version of /remote-home1/yli/Model/Generator/Qwen2.5/7B/base on the 2wikimultihopqa_train, the hotpotqa_train and the musique_train datasets. It achieves the following results on the evaluation set:

  • Loss: 0.1620

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: 7e-06
  • train_batch_size: 4
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 8
  • 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: 3.0

Training results

Training LossEpochStepValidation Loss
0.16540.39945000.1538
0.15310.798710000.1395
0.09381.198115000.1406
0.09481.597420000.1360
0.08441.996825000.1315
0.04182.396230000.1611
0.03792.795535000.1621

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.4.0
  • Datasets 3.1.0
  • Tokenizers 0.20.3
conversational
endpoints_compatible
full
generated_from_trainer
llama-factory
qwen2
safetensors
text-generation
text-generation-inference
transformers

Yuan-Li-FNLP/R3-RAG-CS-Qwen

Model

should probably proofread and complete it, then remove this comment. -->

1

2 commits

1 linked in READMEs

updated May 26, 2025

See the code

README

qwen

This model is a fine-tuned version of /remote-home1/yli/Model/Generator/Qwen2.5/7B/base on the 2wikimultihopqa_train, the hotpotqa_train and the musique_train datasets. It achieves the following results on the evaluation set:

  • Loss: 0.1620

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: 7e-06
  • train_batch_size: 4
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 8
  • 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: 3.0

Training results

Training LossEpochStepValidation Loss
0.16540.39945000.1538
0.15310.798710000.1395
0.09381.198115000.1406
0.09481.597420000.1360
0.08441.996825000.1315
0.04182.396230000.1611
0.03792.795535000.1621

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.4.0
  • Datasets 3.1.0
  • Tokenizers 0.20.3
conversational
endpoints_compatible
full
generated_from_trainer
llama-factory
qwen2
safetensors
text-generation
text-generation-inference
transformers