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: 0.6109

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: 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: 550

Training results

Training Loss	Epoch	Step	Validation Loss
0.6471	0.0447	50	0.6717
0.6632	0.0895	100	0.7106
0.6331	0.1342	150	0.6956
0.6753	0.1790	200	0.6720
0.6431	0.2237	250	0.6651
0.587	0.2685	300	0.6481
0.6242	0.3132	350	0.6331
0.587	0.3579	400	0.6210
0.6157	0.4027	450	0.6128
0.57	0.4474	500	0.6110
0.5725	0.4922	550	0.6109

Framework versions

Transformers 4.42.3
Pytorch 2.0.0+cu117
Datasets 2.20.0
Tokenizers 0.19.1

RichardErkhov/tsavage68_-_Summary4500_L3_550steps_1e5rate_SFT-4bits

Original model description:

Summary4500_L3_550steps_1e5rate_SFT

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
tsavage68_-_Summary4500_L3_550steps_1e5rate_SFT-4bits