metadata

license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: Qwen/Qwen2-7B
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: QWEN_2_7B_MT
    results: []

QWEN_2_7B_MT

This model is a fine-tuned version of Qwen/Qwen2-7B on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7702
Accuracy: 0.78
Precision: 0.7979
Recall: 0.75
F1 score: 0.7732

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1 score
0.93	0.25	200	0.8818	0.6517	0.7264	0.4867	0.5828
0.6783	0.5	400	1.1545	0.59	0.7411	0.2767	0.4029
0.6849	0.75	600	0.7826	0.685	0.7424	0.5667	0.6427
0.6378	1.0	800	0.7399	0.695	0.7647	0.5633	0.6488
0.4773	1.25	1000	0.9978	0.66	0.8077	0.42	0.5526
0.4842	1.5	1200	0.6576	0.7333	0.6902	0.8467	0.7605
0.456	1.75	1400	0.6290	0.77	0.8068	0.71	0.7553
0.464	2.0	1600	0.6295	0.7617	0.7774	0.7333	0.7547
0.3689	2.25	1800	0.6090	0.7783	0.8224	0.71	0.7621
0.307	2.5	2000	0.6058	0.7733	0.7808	0.76	0.7703
0.3302	2.75	2200	0.6024	0.7867	0.7810	0.7967	0.7888
0.3156	3.0	2400	0.7082	0.765	0.8272	0.67	0.7403
0.2571	3.25	2600	0.9494	0.7017	0.8168	0.52	0.6354
0.2593	3.5	2800	0.6498	0.7717	0.8030	0.72	0.7592
0.2458	3.75	3000	0.6434	0.7867	0.7810	0.7967	0.7888
0.2135	4.0	3200	0.7042	0.775	0.7978	0.7367	0.7660
0.1582	4.25	3400	0.6730	0.78	0.7530	0.8333	0.7911
0.158	4.5	3600	0.7538	0.7783	0.8104	0.7267	0.7663
0.2043	4.75	3800	0.7398	0.785	0.8065	0.75	0.7772
0.163	5.0	4000	0.7702	0.78	0.7979	0.75	0.7732

Framework versions

PEFT 0.11.1
Transformers 4.44.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1