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pythia-1b-kto-iter0-epoch1

This model is a fine-tuned version of DatPySci/pythia-1b-sft-full on the DatPySci/SPIN_iter0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3355
  • Rewards/real: -0.0044
  • Rewards/generated: -1.1080
  • Rewards/accuracies: 0.9600
  • Rewards/margins: 1.1036
  • Logps/generated: -571.6245
  • Logps/real: -468.8171
  • Logits/generated: 0.2235
  • Logits/real: -0.2848

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-07
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • 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: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/real Rewards/generated Rewards/accuracies Rewards/margins Logps/generated Logps/real Logits/generated Logits/real
0.4016 0.38 300 0.3914 0.0270 -0.8143 0.9320 0.8413 -568.6872 -468.5030 0.2573 -0.2517
0.3451 0.77 600 0.3355 -0.0044 -1.1080 0.9600 1.1036 -571.6245 -468.8171 0.2235 -0.2848

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.2.1
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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