You can deploy this model and start earning money today!

sizhkhy/
restaurant365

Name: restaurant365
Availability: InStock

generated_from_trainer

unsloth/Llama-3.2-3B-Instruct

adapter

other

Views

No views yet

llm3br256

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the restaurant365 dataset. It achieves the following results on the evaluation set:

Loss: 0.0010

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: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 25.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.0179	0.0808	25	0.0179
0.0102	0.1616	50	0.0122
0.0117	0.2424	75	0.0097
0.0094	0.3232	100	0.0083
0.0089	0.4040	125	0.0074
0.0071	0.4848	150	0.0067
0.0075	0.5657	175	0.0065
0.0055	0.6465	200	0.0061
0.0089	0.7273	225	0.0057
0.0035	0.8081	250	0.0053
0.0054	0.8889	275	0.0050
0.0031	0.9697	300	0.0047
0.0048	1.0505	325	0.0044
0.0027	1.1313	350	0.0043
0.0033	1.2121	375	0.0042
0.004	1.2929	400	0.0041
0.0035	1.3737	425	0.0040
0.003	1.4545	450	0.0035
0.0025	1.5354	475	0.0035
0.0042	1.6162	500	0.0032
0.0027	1.6970	525	0.0031
0.0031	1.7778	550	0.0029
0.0015	1.8586	575	0.0029
0.0032	1.9394	600	0.0029
0.0018	2.0202	625	0.0031
0.0018	2.1010	650	0.0026
0.0017	2.1818	675	0.0028
0.0016	2.2626	700	0.0024
0.0018	2.3434	725	0.0026
0.0025	2.4242	750	0.0022
0.0029	2.5051	775	0.0024
0.0017	2.5859	800	0.0023
0.0014	2.6667	825	0.0021
0.0015	2.7475	850	0.0021
0.0017	2.8283	875	0.0020
0.0018	2.9091	900	0.0018
0.0012	2.9899	925	0.0018
0.0008	3.0707	950	0.0018
0.0011	3.1515	975	0.0017
0.0012	3.2323	1000	0.0017
0.0008	3.3131	1025	0.0017
0.0013	3.3939	1050	0.0015
0.0015	3.4747	1075	0.0015
0.0006	3.5556	1100	0.0015
0.0011	3.6364	1125	0.0014
0.0014	3.7172	1150	0.0014
0.0011	3.7980	1175	0.0014
0.0009	3.8788	1200	0.0014
0.0005	3.9596	1225	0.0014
0.0005	4.0404	1250	0.0014
0.001	4.1212	1275	0.0013
0.0011	4.2020	1300	0.0013
0.0007	4.2828	1325	0.0014
0.0007	4.3636	1350	0.0014
0.0006	4.4444	1375	0.0013
0.0008	4.5253	1400	0.0012
0.0008	4.6061	1425	0.0012
0.0006	4.6869	1450	0.0012
0.0006	4.7677	1475	0.0012
0.0007	4.8485	1500	0.0012
0.0009	4.9293	1525	0.0011
0.0004	5.0101	1550	0.0011
0.0003	5.0909	1575	0.0011
0.0007	5.1717	1600	0.0010
0.0005	5.2525	1625	0.0011
0.0005	5.3333	1650	0.0010
0.0004	5.4141	1675	0.0010
0.0005	5.4949	1700	0.0010
0.0004	5.5758	1725	0.0013

Framework versions

PEFT 0.12.0
Transformers 4.46.1
Pytorch 2.4.0+cu121
Datasets 3.1.0
Tokenizers 0.20.3

sizhkhy/restaurant365

llm3br256

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sizhkhy/
restaurant365