This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the preference-data dataset. It achieves the following results on the evaluation set:

Loss: 1.1019

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: 4
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.0662	0.9986	180	1.1019

Framework versions

PEFT 0.11.1
Transformers 4.43.4
Pytorch 2.3.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1

terry69/downstream-7b-p0.1_seed42_syntax_level1

downstream-7b-p0.1_seed42_syntax_level1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

terry69/
downstream-7b-p0.1_seed42_syntax_level1