This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the APIGen_5k_arguments_fixed_hermes_corrected dataset. It achieves the following results on the evaluation set:

Loss: 0.5013

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: 12

Training results

Training Loss	Epoch	Step	Validation Loss
0.1514	1.4365	300	0.1778
0.0842	2.8729	600	0.1907
0.0307	4.3070	900	0.2594
0.0154	5.7434	1200	0.3033
0.0036	7.1775	1500	0.3796
0.002	8.6139	1800	0.4437
0.0007	10.0480	2100	0.4878
0.0003	11.4844	2400	0.5003

Framework versions

Transformers 4.51.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

lemonhat/Qwen2.5-7B-Instruct-APIGen_5k_arguments_fixed_hermes_corrected

APIGen_5k_arguments_fixed_hermes_corrected

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lemonhat/
Qwen2.5-7B-Instruct-APIGen_5k_arguments_fixed_hermes_corrected