This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the C1_15k_tag5_cleaned_hermes dataset. It achieves the following results on the evaluation set:

Loss: 0.2391

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
0.2796	0.1170	100	0.2980
0.2733	0.2339	200	0.2810
0.3045	0.3509	300	0.2678
0.2478	0.4678	400	0.2592
0.2403	0.5848	500	0.2496
0.2216	0.7018	600	0.2460
0.26	0.8187	700	0.2421
0.2469	0.9357	800	0.2395

Framework versions

Transformers 4.46.1
Pytorch 2.6.0+cu124
Datasets 3.1.0
Tokenizers 0.20.3

lemonhat/Qwen2.5-7B-Instruct-C1_15k_tag5_cleaned_hermes

C1_15k_tag5_cleaned_hermes

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lemonhat/
Qwen2.5-7B-Instruct-C1_15k_tag5_cleaned_hermes