MetaMath-Cybertron-Starling-Ruby

This model is a fine-tuned version of Q-bert/MetaMath-Cybertron-Starling on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0319

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• lr_scheduler_warmup_steps: 1
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.0913	0.39	50	1.0976
1.0399	0.78	100	1.0319

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1