M6_cross

S2312dal/M6_cross

M6_cross is a text classification model from S2312dal. Use it when you need a label for a piece of text. 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. --

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Hugging Face

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Jun 17, 2022
Updated: Jun 18, 2022
SHA: 6242a1fe

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Model card

From the Hugging Face model README

M6_cross

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: 0.0084
Pearson: 0.9811
Spearmanr: 0.9075

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: 20
eval_batch_size: 20
seed: 25
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 6.0
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Pearson	Spearmanr
0.0059	1.0	105	0.0158	0.9633	0.9054
0.001	2.0	210	0.0102	0.9770	0.9103
0.0008	3.0	315	0.0083	0.9805	0.9052
0.0011	4.0	420	0.0075	0.9812	0.9082
0.0017	5.0	525	0.0084	0.9811	0.9075

Framework versions

Transformers 4.20.0
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jun 17, 2022
Updated: Jun 18, 2022