all_tasks_combined_70b_lora_more_epochs

This model is a fine-tuned version of meta-llama/Meta-Llama-3-70B-Instruct on the identity and the data_mc_filtered datasets. It achieves the following results on the evaluation set:

• Loss: 0.3198

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: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• total_eval_batch_size: 8
• 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_ratio: 0.1
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.2724	0.7428	200	0.3219
0.2418	1.4828	400	0.3126
0.1724	2.2228	600	0.3189
0.1525	2.9656	800	0.3199

Framework versions

• PEFT 0.12.0
• Transformers 4.49.0
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0