Hub-Report-20240803105920

This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2013
• F1: 0.7324
• Roc Auc: 0.8398
• Accuracy: 0.7131

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: 2e-05
• 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: 13

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
No log	1.0	277	0.3087	0.2615	0.5753	0.1530
0.351	2.0	554	0.2457	0.5623	0.7097	0.4357
0.351	3.0	831	0.2093	0.7073	0.8021	0.6245
0.2034	4.0	1108	0.1998	0.6943	0.8009	0.6276
0.2034	5.0	1385	0.1942	0.7220	0.8252	0.6793
0.1504	6.0	1662	0.1938	0.7205	0.8312	0.6962
0.1504	7.0	1939	0.1952	0.7262	0.8366	0.7078
0.1165	8.0	2216	0.2013	0.7324	0.8398	0.7131
0.1165	9.0	2493	0.2077	0.7130	0.8325	0.7036
0.0956	10.0	2770	0.2041	0.7203	0.8359	0.7078
0.0816	11.0	3047	0.2077	0.7250	0.8396	0.7141
0.0816	12.0	3324	0.2122	0.7148	0.8352	0.7078
0.0708	13.0	3601	0.2112	0.7174	0.8361	0.7068

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1