Finetuned_Final_LM_200k_v3

ManojAlexender/Finetuned_Final_LM_200k_v3

Finetuned_Final_LM_200k_v3 is a text classification model from ManojAlexender. Use it when you need a label for a piece of text. It is set up for transformers.

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

Downloads · 30 days

19% of all-time downloads

All-time downloads

Public

Parameters

125M

10.5 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors499 MB · 99%

At a glance

Task: Text Classification
Library: transformers
Model type: roberta
Access: Public
Created: Feb 15, 2024
Updated: Feb 15, 2024
SHA: 8a64e50c

Try a prompt

Model card

From the Hugging Face model README

Finetuned_Final_LM_200k_v3

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.4006
Accuracy: 0.8429
F1: 0.8410
Precision: 0.8602
Recall: 0.8429

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: 5e-05
train_batch_size: 16
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.038	0.08	500	1.6709	0.8505	0.8483	0.8713	0.8505
0.3847	0.16	1000	2.0643	0.8403	0.8385	0.8556	0.8403
0.4135	0.24	1500	1.7622	0.8429	0.8399	0.8706	0.8429
0.3496	0.32	2000	2.2005	0.8482	0.8459	0.8701	0.8482
0.2201	0.4	2500	2.2234	0.8467	0.8445	0.8673	0.8467
0.306	0.48	3000	2.0981	0.8395	0.8375	0.8567	0.8395
0.2741	0.56	3500	2.4972	0.8421	0.8401	0.8607	0.8421
0.2189	0.64	4000	2.1950	0.8459	0.8440	0.8641	0.8459
0.1442	0.72	4500	2.3179	0.8418	0.8399	0.8589	0.8418
0.3744	0.8	5000	2.3932	0.8395	0.8376	0.8565	0.8395
0.2153	0.88	5500	2.3213	0.8406	0.8384	0.8601	0.8406
0.3273	0.96	6000	2.2511	0.8467	0.8444	0.8682	0.8467
0.0371	1.04	6500	2.4062	0.8406	0.8388	0.8573	0.8406
0.1964	1.12	7000	2.3856	0.8421	0.8401	0.8604	0.8421
0.3516	1.2	7500	2.3023	0.8444	0.8424	0.8631	0.8444
0.1166	1.28	8000	2.3752	0.8414	0.8394	0.8594	0.8414
0.2922	1.36	8500	2.4364	0.8425	0.8405	0.8612	0.8425
0.2452	1.44	9000	2.3738	0.8421	0.8402	0.8599	0.8421
0.1247	1.52	9500	2.4287	0.8421	0.8401	0.8604	0.8421
0.0475	1.6	10000	2.4438	0.8433	0.8413	0.8610	0.8433
0.2052	1.68	10500	2.4006	0.8429	0.8410	0.8602	0.8429

Framework versions

Transformers 4.37.0
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1

Task: Text Classification
Library: transformers
Type: roberta
Created: Feb 15, 2024
Updated: Feb 15, 2024