chess-finetune-output

This model is a fine-tuned version of on an unknown dataset.

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-05
• train_batch_size: 200
• eval_batch_size: 200
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 1600
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.05
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 5.2.0
• Pytorch 2.7.1+cu118
• Datasets 4.4.1
• Tokenizers 0.22.1