This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the combined_airline_retail_data dataset. It achieves the following results on the evaluation set:

Loss: 0.2036

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: 5e-06
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 4
total_eval_batch_size: 4
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.4493	0.0569	100	0.2896
0.248	0.1138	200	0.2588
0.3164	0.1706	300	0.2447
0.2388	0.2275	400	0.2337
0.2886	0.2844	500	0.2312
0.2529	0.3413	600	0.2250
0.1868	0.3982	700	0.2235
0.3634	0.4551	800	0.2203
0.2655	0.5119	900	0.2157
0.188	0.5688	1000	0.2115
0.2229	0.6257	1100	0.2081
0.2813	0.6826	1200	0.2065
0.2193	0.7395	1300	0.2069
0.2872	0.7964	1400	0.2058
0.3175	0.8532	1500	0.2049
0.195	0.9101	1600	0.2037
0.2504	0.9670	1700	0.2037

Framework versions

Transformers 4.46.1
Pytorch 2.6.0+cu124
Datasets 3.1.0
Tokenizers 0.20.3

lemonhat/Qwen2.5-1.5B-Instruct-combined_airline_retail_data

combined_airline_retail_data

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lemonhat/
Qwen2.5-1.5B-Instruct-combined_airline_retail_data