local_distilbert_finetune_model

Senthilkumar-M/local_distilbert_finetune_model

local_distilbert_finetune_model is a token classification model from Senthilkumar-M. Use it when you need labels on individual words, such as names. 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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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Feb 21, 2024
Updated: Feb 28, 2024
SHA: 308fa5ab

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Base models

Model card

From the Hugging Face model README

local_distilbert_finetune_model

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

Loss: 0.2154
Precision: 0.5
Recall: 0.5
F1: 0.5
Accuracy: 0.9231

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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	1	0.8718	0.0	0.0	0.0	0.7692
No log	2.0	2	0.8088	0.0	0.0	0.0	0.7692
No log	3.0	3	0.7507	0.0	0.0	0.0	0.7692
No log	4.0	4	0.6957	0.0	0.0	0.0	0.7692
No log	5.0	5	0.6445	0.0	0.0	0.0	0.7692
No log	6.0	6	0.5982	0.0	0.0	0.0	0.7692
No log	7.0	7	0.5559	0.0	0.0	0.0	0.7692
No log	8.0	8	0.5177	0.0	0.0	0.0	0.7692
No log	9.0	9	0.4832	0.0	0.0	0.0	0.8462
No log	10.0	10	0.4523	0.5	0.5	0.5	0.9231
No log	11.0	11	0.4243	0.5	0.5	0.5	0.9231
No log	12.0	12	0.3996	0.5	0.5	0.5	0.9231
No log	13.0	13	0.3778	0.5	0.5	0.5	0.9231
No log	14.0	14	0.3592	0.5	0.5	0.5	0.9231
No log	15.0	15	0.3428	0.5	0.5	0.5	0.9231
No log	16.0	16	0.3293	0.5	0.5	0.5	0.9231
No log	17.0	17	0.3180	0.5	0.5	0.5	0.9231
No log	18.0	18	0.3087	0.5	0.5	0.5	0.9231
No log	19.0	19	0.3003	0.5	0.5	0.5	0.9231
No log	20.0	20	0.2933	0.5	0.5	0.5	0.9231
No log	21.0	21	0.2865	0.5	0.5	0.5	0.9231
No log	22.0	22	0.2807	0.5	0.5	0.5	0.9231
No log	23.0	23	0.2755	0.5	0.5	0.5	0.9231
No log	24.0	24	0.2689	0.5	0.5	0.5	0.9231
No log	25.0	25	0.2628	0.5	0.5	0.5	0.9231
No log	26.0	26	0.2573	0.5	0.5	0.5	0.9231
No log	27.0	27	0.2528	0.5	0.5	0.5	0.9231
No log	28.0	28	0.2487	0.5	0.5	0.5	0.9231
No log	29.0	29	0.2451	0.5	0.5	0.5	0.9231
No log	30.0	30	0.2420	0.5	0.5	0.5	0.9231
No log	31.0	31	0.2392	0.5	0.5	0.5	0.9231
No log	32.0	32	0.2363	0.5	0.5	0.5	0.9231
No log	33.0	33	0.2335	0.5	0.5	0.5	0.9231
No log	34.0	34	0.2310	0.5	0.5	0.5	0.9231
No log	35.0	35	0.2288	0.5	0.5	0.5	0.9231
No log	36.0	36	0.2267	0.5	0.5	0.5	0.9231
No log	37.0	37	0.2247	0.5	0.5	0.5	0.9231
No log	38.0	38	0.2230	0.5	0.5	0.5	0.9231
No log	39.0	39	0.2216	0.5	0.5	0.5	0.9231
No log	40.0	40	0.2205	0.5	0.5	0.5	0.9231
No log	41.0	41	0.2196	0.5	0.5	0.5	0.9231
No log	42.0	42	0.2187	0.5	0.5	0.5	0.9231
No log	43.0	43	0.2180	0.5	0.5	0.5	0.9231
No log	44.0	44	0.2173	0.5	0.5	0.5	0.9231
No log	45.0	45	0.2168	0.5	0.5	0.5	0.9231
No log	46.0	46	0.2163	0.5	0.5	0.5	0.9231
No log	47.0	47	0.2159	0.5	0.5	0.5	0.9231
No log	48.0	48	0.2157	0.5	0.5	0.5	0.9231
No log	49.0	49	0.2155	0.5	0.5	0.5	0.9231
No log	50.0	50	0.2154	0.5	0.5	0.5	0.9231

Framework versions

Transformers 4.38.1
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Feb 21, 2024
Updated: Feb 28, 2024