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: 1.9216

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-07
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: 625

Training results

Training Loss	Epoch	Step	Validation Loss
2.4485	0.3333	25	2.4666
2.4645	0.6667	50	2.4522
2.452	1.0	75	2.4164
2.391	1.3333	100	2.3529
2.2825	1.6667	125	2.2874
2.1758	2.0	150	2.2259
2.2189	2.3333	175	2.1723
2.1642	2.6667	200	2.1247
2.1223	3.0	225	2.0833
2.0341	3.3333	250	2.0461
1.9642	3.6667	275	2.0153
1.998	4.0	300	1.9903
2.0321	4.3333	325	1.9697
1.9443	4.6667	350	1.9542
1.9787	5.0	375	1.9421
1.9403	5.3333	400	1.9349
1.9464	5.6667	425	1.9279
1.9067	6.0	450	1.9245
1.927	6.3333	475	1.9228
1.8829	6.6667	500	1.9220
1.9613	7.0	525	1.9229
1.9701	7.3333	550	1.9218
1.9411	7.6667	575	1.9217
1.9127	8.0	600	1.9216
1.9497	8.3333	625	1.9216

Framework versions

Transformers 4.41.2
Pytorch 2.0.0+cu117
Datasets 2.19.2
Tokenizers 0.19.1

tsavage68/UTI_L3_625steps_1e7rate_SFT

UTI_L3_625steps_1e7rate_SFT

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tsavage68/
UTI_L3_625steps_1e7rate_SFT