model1-thesis-2

UchihaMadara/model1-thesis-2

model1-thesis-2 is a token classification model from UchihaMadara. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

2% of all-time downloads

All-time downloads

326

Public

Repo size

3 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin436 MB · 100%

At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Feb 6, 2023
Updated: Feb 6, 2023
SHA: b0bc4c34

Try a prompt

Model card

From the Hugging Face model README

model1-thesis-2

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2895
Precision: 0.3090
Recall: 0.3740
F1: 0.3384
Accuracy: 0.4889

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-05
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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	12	1.4038	0.1997	0.1653	0.1809	0.4624
No log	2.0	24	1.3086	0.2769	0.2777	0.2773	0.4911
No log	3.0	36	1.2895	0.3090	0.3740	0.3384	0.4889

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 6, 2023
Updated: Feb 6, 2023