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rm1

This model is a fine-tuned version of EleutherAI/pythia-160m on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5286
  • Accuracy: 0.8456

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: 3e-06
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6883 0.0621 5 0.6846 0.7537
0.6723 0.1242 10 0.6717 0.7978
0.6761 0.1863 15 0.6559 0.8162
0.6627 0.2484 20 0.6379 0.8125
0.6156 0.3104 25 0.6175 0.8125
0.6232 0.3725 30 0.5937 0.8272
0.5985 0.4346 35 0.5711 0.8456
0.6024 0.4967 40 0.5549 0.8309
0.5906 0.5588 45 0.5449 0.8346
0.6184 0.6209 50 0.5383 0.8419
0.5379 0.6830 55 0.5338 0.8382
0.564 0.7451 60 0.5312 0.8456
0.5635 0.8071 65 0.5299 0.8456
0.5892 0.8692 70 0.5292 0.8493
0.5416 0.9313 75 0.5288 0.8456
0.5994 0.9934 80 0.5286 0.8456

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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