llama-3.2-350M-fourier

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llama-3.2-350M-fourier

This model is a fine-tuned version of llama_small_config.json on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.5784

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: 0.0005
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 16
• total_train_batch_size: 64
• total_eval_batch_size: 4
• optimizer: Use 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: 1000
• num_epochs: 1

Training results

Framework versions

• Transformers 4.48.2
• Pytorch 2.3.1+cu118
• Datasets 3.2.0
• Tokenizers 0.21.0