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metadata
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
  - llama-factory
  - full
  - generated_from_trainer
model-index:
  - name: prm_version3_full_hf
    results: []

prm_version3_full_hf

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the prm_conversations_prm_version3_math+webinstructsub-mcq+webinstructsub-oe+apps+gsm_mix_ref_hf dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1166

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: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
0.1961 0.0461 500 0.2069
0.192 0.0921 1000 0.1930
0.1963 0.1382 1500 0.1833
0.1701 0.1843 2000 0.1748
0.1647 0.2303 2500 0.1687
0.1507 0.2764 3000 0.1630
0.1421 0.3225 3500 0.1579
0.1403 0.3685 4000 0.1528
0.1557 0.4146 4500 0.1485
0.1536 0.4607 5000 0.1441
0.1344 0.5067 5500 0.1399
0.1195 0.5528 6000 0.1355
0.1209 0.5989 6500 0.1316
0.137 0.6450 7000 0.1284
0.117 0.6910 7500 0.1253
0.116 0.7371 8000 0.1228
0.1259 0.7832 8500 0.1206
0.1147 0.8292 9000 0.1187
0.1175 0.8753 9500 0.1175
0.1117 0.9214 10000 0.1168
0.1133 0.9674 10500 0.1166

Framework versions

  • Transformers 4.45.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3