reward-model-out

This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.6737
  • eval_accuracy: 0.6041
  • eval_precision: 0.6041
  • eval_recall: 1.0
  • eval_f1: 0.7532
  • eval_runtime: 23.9877
  • eval_samples_per_second: 32.85
  • eval_steps_per_second: 5.503
  • epoch: 0.35
  • step: 4500

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: 0.0001
  • train_batch_size: 6
  • eval_batch_size: 6
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Framework versions

  • Transformers 4.35.0.dev0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.14.1
Downloads last month
24
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for satpalsr/the-beginning

Finetuned
(254)
this model