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metadata
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
  - alignment-handbook
  - trl
  - dpo
  - generated_from_trainer
  - trl
  - dpo
  - generated_from_trainer
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
model-index:
  - name: zephyr-7b-align-scan-9e-07-0.86-linear-2.0
    results: []

zephyr-7b-align-scan-9e-07-0.86-linear-2.0

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2207
  • Rewards/chosen: 0.7526
  • Rewards/rejected: -1.3224
  • Rewards/accuracies: 0.3294
  • Rewards/margins: 2.0750
  • Logps/rejected: -82.6661
  • Logps/chosen: -73.6161
  • Logits/rejected: -2.6026
  • Logits/chosen: -2.6190

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: 9e-07
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.9734 0.3484 100 0.9203 2.0652 1.3351 0.3294 0.7302 -79.5760 -72.0898 -2.5695 -2.5853
0.9883 0.6969 200 1.0967 2.4271 1.1885 0.3373 1.2386 -79.7464 -71.6691 -2.5708 -2.5875
0.4215 1.0453 300 1.1234 3.0876 1.7905 0.3313 1.2970 -79.0463 -70.9010 -2.6403 -2.6560
0.393 1.3937 400 1.2234 -0.1343 -1.8934 0.3234 1.7591 -83.3299 -74.6474 -2.6093 -2.6250
0.3986 1.7422 500 1.2247 0.1937 -1.8484 0.3214 2.0420 -83.2776 -74.2660 -2.5909 -2.6070

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1