RobertaBaseUnprocessedDownsampledKeyword

ImperialIndians23/RobertaBaseUnprocessedDownsampledKeyword

RobertaBaseUnprocessedDownsampledKeyword is a machine learning model from ImperialIndians23. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.

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

Downloads · 30 days

Access

Public

Updated Mar 2, 2024

Parameters

125M

3 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors499 MB · 100%

At a glance

License: mit
Access: Public
Created: Mar 2, 2024
Updated: Mar 2, 2024
SHA: f132c9f7

Base models

Model card

From the Hugging Face model README

RobertaBaseUnprocessedDownsampledKeyword

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

Loss: 0.2552
Accuracy: 0.8863
F1: 0.4979
Precision: 0.4291
Recall: 0.5930

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: 1e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: inverse_sqrt
lr_scheduler_warmup_steps: 500
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4399	1.0	297	0.5145	0.7292	0.3693	0.2371	0.8342
0.3785	2.0	595	0.2552	0.8863	0.4979	0.4291	0.5930
0.3222	2.99	891	0.3002	0.8591	0.4957	0.3756	0.7286

Framework versions

Transformers 4.38.2
Pytorch 2.1.2+cu121
Datasets 2.17.1
Tokenizers 0.15.2

License: mit
Created: Mar 2, 2024
Updated: Mar 2, 2024