This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the NEW3_t1_5k_tag5 dataset. It achieves the following results on the evaluation set:

Loss: 0.2068

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss
0.3071	0.2242	100	0.2587
0.3309	0.4484	200	0.2410
0.3571	0.6726	300	0.2315
0.1996	0.8969	400	0.2278
0.2253	1.1211	500	0.2183
0.2125	1.3453	600	0.2126
0.2466	1.5695	700	0.2113
0.2103	1.7937	800	0.2072

Framework versions

Transformers 4.46.1
Pytorch 2.6.0+cu124
Datasets 3.1.0
Tokenizers 0.20.3

lemonhat/Qwen2.5-7B-Instruct-NEW3_t1_5k_tag5

NEW3_t1_5k_tag5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lemonhat/
Qwen2.5-7B-Instruct-NEW3_t1_5k_tag5