SciBERT_25K_steps_higherlr_bs64

bdpc/SciBERT_25K_steps_higherlr_bs64

SciBERT_25K_steps_higherlr_bs64 is a text classification model from bdpc. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: Feb 5, 2024
Updated: Feb 6, 2024
SHA: 72ac85ba

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Base models

allenai/scibert_scivocab_uncased

Model card

From the Hugging Face model README

SciBERT_25K_steps_higherlr_bs64

This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0485
Accuracy: 0.9902
Precision: 0.0
Recall: 0.0
F1: 0.0
Hamming: 0.0098

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: 0.0005
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 25000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Hamming
0.0488	0.16	5000	0.0489	0.9902	0.0098
0.0486	0.32	10000	0.0488	0.9902	0.0098
0.0484	0.47	15000	0.0488	0.9902	0.0098
0.0482	0.63	20000	0.0485	0.9902	0.0098
0.0481	0.79	25000	0.0485	0.9902	0.0098

Framework versions

Transformers 4.33.3
Pytorch 2.2.0.dev20231002
Datasets 2.7.1
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
Created: Feb 5, 2024
Updated: Feb 6, 2024