BERT_V8_sp10_lw40_ex50_lo100_k2_k2_fold0

genki10/BERT_V8_sp10_lw40_ex50_lo100_k2_k2_fold0

BERT_V8_sp10_lw40_ex50_lo100_k2_k2_fold0 is a text classification model from genki10. 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

10% of all-time downloads

All-time downloads

Public

Repo size

16.6 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin876 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Apr 26, 2025
Updated: Apr 26, 2025
SHA: 3a5d4376

Try a prompt

Base models

Model card

From the Hugging Face model README

BERT_V8_sp10_lw40_ex50_lo100_k2_k2_fold0

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9195
Qwk: 0.4088
Mse: 0.9195
Rmse: 0.9589

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: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	8.8386	0.0	8.8386	2.9730
No log	2.0	4	7.7632	0.0	7.7632	2.7862
No log	3.0	6	6.7667	0.0	6.7667	2.6013
No log	4.0	8	5.9342	0.0173	5.9342	2.4360
No log	5.0	10	5.1408	0.0115	5.1408	2.2673
No log	6.0	12	4.3138	0.0039	4.3138	2.0770
No log	7.0	14	3.5581	0.0	3.5581	1.8863
No log	8.0	16	2.7541	0.0	2.7541	1.6595
No log	9.0	18	2.1259	0.0789	2.1259	1.4580
No log	10.0	20	1.6766	0.0316	1.6766	1.2948
No log	11.0	22	1.3311	0.0316	1.3311	1.1537
No log	12.0	24	1.0849	0.0316	1.0849	1.0416
No log	13.0	26	0.9347	0.0316	0.9347	0.9668
No log	14.0	28	0.7951	0.3610	0.7951	0.8917
No log	15.0	30	0.6911	0.4493	0.6911	0.8313
No log	16.0	32	1.0486	0.1661	1.0486	1.0240
No log	17.0	34	0.6671	0.5030	0.6671	0.8167
No log	18.0	36	0.7930	0.4413	0.7930	0.8905
No log	19.0	38	0.8961	0.4233	0.8961	0.9466
No log	20.0	40	0.5172	0.5297	0.5172	0.7192
No log	21.0	42	0.6651	0.5234	0.6651	0.8155
No log	22.0	44	1.3190	0.2865	1.3190	1.1485
No log	23.0	46	0.6246	0.4879	0.6246	0.7903
No log	24.0	48	0.6997	0.4664	0.6997	0.8365
No log	25.0	50	0.6324	0.4273	0.6324	0.7952
No log	26.0	52	0.6438	0.4628	0.6438	0.8024
No log	27.0	54	1.0050	0.3500	1.0050	1.0025
No log	28.0	56	0.8972	0.3736	0.8972	0.9472
No log	29.0	58	0.6973	0.4445	0.6973	0.8350
No log	30.0	60	0.7448	0.4582	0.7448	0.8630
No log	31.0	62	0.7564	0.4181	0.7564	0.8697
No log	32.0	64	0.8068	0.4132	0.8068	0.8982
No log	33.0	66	0.8694	0.4142	0.8694	0.9324
No log	34.0	68	0.8131	0.4003	0.8131	0.9017
No log	35.0	70	0.8644	0.4034	0.8644	0.9297
No log	36.0	72	0.8810	0.4100	0.8810	0.9386
No log	37.0	74	0.8224	0.4044	0.8224	0.9069
No log	38.0	76	0.9413	0.3429	0.9413	0.9702
No log	39.0	78	0.7832	0.4248	0.7832	0.8850
No log	40.0	80	0.8008	0.4215	0.8008	0.8949
No log	41.0	82	0.8348	0.4022	0.8348	0.9137
No log	42.0	84	0.8612	0.3882	0.8612	0.9280
No log	43.0	86	0.8992	0.4052	0.8992	0.9483
No log	44.0	88	0.8836	0.3976	0.8836	0.9400
No log	45.0	90	0.8058	0.4452	0.8058	0.8976
No log	46.0	92	0.7889	0.4430	0.7889	0.8882
No log	47.0	94	0.9072	0.3687	0.9072	0.9525
No log	48.0	96	0.9227	0.3774	0.9227	0.9606
No log	49.0	98	0.8276	0.4230	0.8276	0.9097
No log	50.0	100	0.9195	0.4088	0.9195	0.9589

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Apr 26, 2025
Updated: Apr 26, 2025