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pythia1b-rm-tldr6.9b

This model is a fine-tuned version of mnoukhov/pythia1b-sft-tldr on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4685
  • Accuracy: 0.7693

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: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5365 0.2006 291 0.5420 0.7271
0.4521 0.4011 582 0.5034 0.7485
0.3994 0.6017 873 0.4893 0.7577
0.3596 0.8022 1164 0.4685 0.7693

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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