This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the 2and3_apps_15k_v4_tag5_processed dataset. It achieves the following results on the evaluation set:

Loss: 0.1986

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
gradient_accumulation_steps: 2
total_train_batch_size: 8
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
0.2348	0.1982	100	0.2270
0.2243	0.3964	200	0.2156
0.2081	0.5946	300	0.2044
0.2162	0.7929	400	0.1999
0.2316	0.9911	500	0.1984

Framework versions

Transformers 4.46.1
Pytorch 2.6.0+cu124
Datasets 3.1.0
Tokenizers 0.20.3

lemonhat/Qwen2.5-7B-Instruct-2and3_apps_15k_v4_tag5_processed

2and3_apps_15k_v4_tag5_processed

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lemonhat/
Qwen2.5-7B-Instruct-2and3_apps_15k_v4_tag5_processed