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SmolLM-1.7B-Instruct-dpo-16k

This model is a fine-tuned version of HuggingFaceTB/SmolLM-360M-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8854
  • Rewards/chosen: 0.0056
  • Rewards/rejected: 0.3516
  • Rewards/accuracies: 0.0326
  • Rewards/margins: -0.3460
  • Logps/rejected: -470.7809
  • Logps/chosen: -546.0043
  • Logits/rejected: 0.3165
  • Logits/chosen: 0.6158

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 2
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.5228 0.9999 3368 0.8697 0.0208 0.3405 0.0348 -0.3197 -470.8920 -545.8519 0.3270 0.6295
0.4508 2.0 6737 0.8870 0.0130 0.3621 0.0228 -0.3491 -470.6755 -545.9296 0.2662 0.5778
0.4451 2.9999 10105 0.8871 0.0057 0.3546 0.0337 -0.3489 -470.7502 -546.0029 0.2855 0.5938
0.4447 4.0 13474 0.8869 0.0098 0.3588 0.0196 -0.3490 -470.7085 -545.9620 0.3198 0.6222
0.4446 4.9999 16842 0.8870 0.0065 0.3551 0.0391 -0.3486 -470.7452 -545.9945 0.3097 0.6124
0.4448 5.9991 20208 0.8854 0.0056 0.3516 0.0326 -0.3460 -470.7809 -546.0043 0.3165 0.6158

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.2.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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