metadata

license: apache-2.0
base_model: alex-miller/ODABert
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: cdp-multi-classifier-sub-classes-weighted
    results: []

cdp-multi-classifier-sub-classes-weighted

This model is a fine-tuned version of alex-miller/ODABert. It achieves the following results on the evaluation set:

Loss: 0.6494
Accuracy: 0.8423
F1: 0.7847
Precision: 0.7488
Recall: 0.8243

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-06
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.8824	1.0	206	0.9109	0.6793	0.5494	0.5385	0.5607
0.816	2.0	412	0.8348	0.7865	0.7127	0.6712	0.7597
0.7455	3.0	618	0.7694	0.7712	0.7053	0.64	0.7855
0.6808	4.0	824	0.7323	0.7874	0.7217	0.6638	0.7907
0.6246	5.0	1030	0.6920	0.7829	0.7175	0.6567	0.7907
0.5689	6.0	1236	0.6926	0.7874	0.7230	0.6624	0.7959
0.5237	7.0	1442	0.6642	0.8072	0.7476	0.6876	0.8191
0.4842	8.0	1648	0.6419	0.8081	0.7461	0.6925	0.8088
0.4519	9.0	1854	0.6498	0.8225	0.7612	0.7169	0.8114
0.4264	10.0	2060	0.6496	0.8315	0.7728	0.7294	0.8217
0.4078	11.0	2266	0.6669	0.8378	0.7800	0.7401	0.8243
0.398	12.0	2472	0.6508	0.8405	0.7828	0.7453	0.8243
0.3808	13.0	2678	0.6539	0.8387	0.7809	0.7419	0.8243
0.3757	14.0	2884	0.6497	0.8423	0.7847	0.7488	0.8243
0.3691	15.0	3090	0.6494	0.8423	0.7847	0.7488	0.8243

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1