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metadata
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
tags:
  - summarization
  - generated_from_trainer
model-index:
  - name: sft-sum-chosen-10lp-shuff-full-tiny_same_params
    results: []

sft-sum-chosen-10lp-shuff-full-tiny_same_params

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T on the martimfasantos/openai-summarize-tldr dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8887
  • Nll Loss: 1.8968
  • Logps/best: -71.1814
  • Rewards/chosen: 2.2080
  • Rewards/rejected: -0.6886
  • Rewards/accuracies: 1.0
  • Rewards/margins: 2.8966
  • Logps/rejected: -14.2972
  • Logps/chosen: -71.1814
  • Logits/rejected: -3.0553
  • Logits/chosen: -3.4224

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: 8
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Nll Loss Logps/best Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
1.9469 0.2193 800 1.9582 1.9648 -73.7246 1.9537 -0.4240 1.0 2.3777 -11.6512 -73.7246 -2.7987 -3.1275
1.9813 0.4386 1600 1.9285 1.9369 -72.6769 2.0585 -0.5023 1.0 2.5607 -12.4339 -72.6769 -2.9393 -3.2910
1.9215 0.6579 2400 1.9049 1.9127 -71.7733 2.1488 -0.5719 1.0 2.7207 -13.1300 -71.7733 -3.0198 -3.3812
1.8655 0.8772 3200 1.8887 1.8968 -71.1814 2.2080 -0.6886 1.0 2.8966 -14.2972 -71.1814 -3.0553 -3.4224

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1