Bert_uncased_fine_tuned_Reward_Model

AliChazz/Bert_uncased_fine_tuned_Reward_Model

Bert_uncased_fine_tuned_Reward_Model is a text classification model from AliChazz. 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. --

Downloads · 30 days

2% of all-time downloads

All-time downloads

399

Public

Repo size

5.3 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin438 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 13, 2023
Updated: Mar 13, 2023
SHA: 531d9082

Try a prompt

Datasets

poem_sentiment

Model card

From the Hugging Face model README

Bert_uncased_fine_tuned_Reward_Model

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

Loss: 0.0876
Mse: 0.0876
Mae: 0.1403
R2: 0.7389
Accuracy: 0.875

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: 2e-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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Mae	R2	Accuracy
No log	1.0	53	0.1744	0.1744	0.2973	0.4805	0.7885
No log	2.0	106	0.1074	0.1074	0.2333	0.6801	0.8846
No log	3.0	159	0.1026	0.1026	0.2134	0.6943	0.8654
No log	4.0	212	0.0877	0.0877	0.1841	0.7388	0.8942
No log	5.0	265	0.1000	0.1000	0.2007	0.7021	0.8942
No log	6.0	318	0.0863	0.0863	0.1738	0.7429	0.8942
No log	7.0	371	0.0966	0.0966	0.1827	0.7122	0.8846
No log	8.0	424	0.0946	0.0946	0.1701	0.7183	0.8846
No log	9.0	477	0.0978	0.0978	0.1658	0.7088	0.875
0.0516	10.0	530	0.0854	0.0854	0.1639	0.7457	0.875
0.0516	11.0	583	0.0947	0.0947	0.1620	0.7181	0.8846
0.0516	12.0	636	0.0907	0.0907	0.1516	0.7297	0.8846
0.0516	13.0	689	0.0885	0.0885	0.1546	0.7364	0.875
0.0516	14.0	742	0.0849	0.0849	0.1452	0.7471	0.8942
0.0516	15.0	795	0.0823	0.0823	0.1428	0.7548	0.8846
0.0516	16.0	848	0.0864	0.0864	0.1429	0.7427	0.8846
0.0516	17.0	901	0.0854	0.0854	0.1427	0.7457	0.8846
0.0516	18.0	954	0.0860	0.0860	0.1429	0.7437	0.875
0.0059	19.0	1007	0.0871	0.0871	0.1438	0.7406	0.875
0.0059	20.0	1060	0.0876	0.0876	0.1403	0.7389	0.875

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 13, 2023
Updated: Mar 13, 2023