This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the train_Meta-Llama-3.1-8B-Instruct dataset. It achieves the following results on the evaluation set:

Loss: 0.5039

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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.176	1.9380	500	0.4311

Framework versions

Transformers 4.45.0
Pytorch 2.6.0+cu124
Datasets 2.21.0
Tokenizers 0.20.3

w3en2g/train_llama3_1_8b_legal_aligner8b_add_perference_8ba_3epoch

train_llama3.1_8b_legal_aligner8b_add_perference_8ba_3epoch

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

w3en2g/
train_llama3_1_8b_legal_aligner8b_add_perference_8ba_3epoch