cot-trainset-ft-transduction-v2-lora-train

This model is a fine-tuned version of barc0/cot-400k-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3 on the barc0/cot_train_dataset_960_ms10_v2 and the barc0/cot_rearc_dataset_100_ms10 datasets. It achieves the following results on the evaluation set:

• Loss: 0.1333

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: 0.0002
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• total_eval_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
0.1018	0.9982	277	0.1238
0.0822	1.9964	554	0.1333

Framework versions

• PEFT 0.12.0
• Transformers 4.45.0.dev0
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1