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

Loss: 1.9481

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-06
train_batch_size: 2
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
training_steps: 125

Training results

Training Loss	Epoch	Step	Validation Loss
2.7381	0.3333	25	2.7319
2.5633	0.6667	50	2.4802
2.332	1.0	75	2.1792
1.9781	1.3333	100	2.0001
1.9031	1.6667	125	1.9481

Framework versions

Transformers 4.41.1
Pytorch 2.0.0+cu117
Datasets 2.19.1
Tokenizers 0.19.1

tsavage68/UTI_L3_125steps_1e6rate_SFT

UTI_L3_125steps_1e6rate_SFT

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tsavage68/
UTI_L3_125steps_1e6rate_SFT