Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_fold2

genki10/Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_fold2

Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_fold2 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

8% of all-time downloads

All-time downloads

Public

Repo size

17.5 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 8, 2025
Updated: Apr 8, 2025
SHA: f80d8858

Try a prompt

Base models

Model card

From the Hugging Face model README

Trial3BERT_AugV8_k5_task1_organization_sp010_lw040_fold2

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: 1.0476
Qwk: 0.3806
Mse: 1.0470
Rmse: 1.0232

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 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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	4	12.2487	-0.0017	12.2488	3.4998
No log	2.0	8	7.9586	0.0	7.9589	2.8212
No log	3.0	12	5.3294	0.0117	5.3298	2.3086
No log	4.0	16	3.3056	0.0039	3.3061	1.8183
No log	5.0	20	1.7123	0.0703	1.7127	1.3087
No log	6.0	24	1.1164	0.0107	1.1169	1.0569
No log	7.0	28	0.8425	0.1937	0.8428	0.9181
No log	8.0	32	0.9224	0.0643	0.9227	0.9606
No log	9.0	36	0.9416	0.0685	0.9419	0.9705
No log	10.0	40	0.7391	0.4222	0.7393	0.8598
No log	11.0	44	1.3834	0.2725	1.3834	1.1762
No log	12.0	48	0.5901	0.4726	0.5900	0.7681
No log	13.0	52	0.7922	0.3961	0.7920	0.8899
No log	14.0	56	0.7164	0.3983	0.7160	0.8462
No log	15.0	60	0.5817	0.4766	0.5814	0.7625
No log	16.0	64	0.6065	0.4734	0.6060	0.7784
No log	17.0	68	0.6593	0.5275	0.6585	0.8115
No log	18.0	72	0.7866	0.4850	0.7859	0.8865
No log	19.0	76	0.9128	0.4302	0.9124	0.9552
No log	20.0	80	0.5841	0.4963	0.5837	0.7640
No log	21.0	84	0.7351	0.4012	0.7346	0.8571
No log	22.0	88	0.7501	0.4079	0.7495	0.8657
No log	23.0	92	0.8400	0.4067	0.8394	0.9162
No log	24.0	96	0.8531	0.4055	0.8522	0.9231
No log	25.0	100	1.2159	0.3132	1.2146	1.1021
No log	26.0	104	0.9434	0.3576	0.9423	0.9707
No log	27.0	108	0.8786	0.3675	0.8780	0.9370
No log	28.0	112	1.2836	0.2750	1.2829	1.1327
No log	29.0	116	0.8383	0.4014	0.8375	0.9151
No log	30.0	120	0.7902	0.4091	0.7895	0.8885
No log	31.0	124	0.7264	0.4428	0.7258	0.8519
No log	32.0	128	1.0476	0.3806	1.0470	1.0232

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Apr 8, 2025
Updated: Apr 8, 2025