Fine_Tuning_SC_Method_2_Epoch_13B

VinsmokeMir/Fine_Tuning_SC_Method_2_Epoch_13B

Fine_Tuning_SC_Method_2_Epoch_13B is a text classification model from VinsmokeMir. 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. --

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At a glance

Task: Text Classification
Library: transformers
Model type: bert
Access: Public
Created: May 23, 2023
Updated: May 23, 2023
SHA: 3b12d7ce

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Model card

From the Hugging Face model README

Fine_Tuning_SC_Method_2_Epoch_13B

This model is a fine-tuned version of rafsankabir/Pretrained_E13B_Method2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.4244
Accuracy: 0.6873
F1 Macro: 0.6544

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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 40
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro
No log	1.27	500	1.0673	0.3976	0.1896
1.0138	2.54	1000	0.8217	0.6331	0.5569
1.0138	3.82	1500	0.7889	0.6662	0.6049
0.7305	5.09	2000	0.7821	0.6765	0.6382
0.7305	6.36	2500	0.7867	0.6918	0.6457
0.5856	7.63	3000	0.8236	0.6892	0.6623
0.5856	8.91	3500	0.8490	0.6835	0.6551
0.4723	10.18	4000	0.9057	0.6854	0.6533
0.4723	11.45	4500	0.9237	0.6796	0.6455
0.3896	12.72	5000	0.9814	0.6879	0.6499
0.3896	13.99	5500	0.9984	0.6745	0.6487
0.3299	15.27	6000	1.0226	0.6822	0.6545
0.3299	16.54	6500	1.0579	0.6758	0.6485
0.2783	17.81	7000	1.0932	0.6796	0.6487
0.2783	19.08	7500	1.1047	0.6950	0.6609
0.2455	20.36	8000	1.1643	0.6860	0.6559
0.2455	21.63	8500	1.1953	0.6841	0.6548
0.2181	22.9	9000	1.2043	0.6835	0.6516
0.2181	24.17	9500	1.2603	0.6867	0.6502
0.1894	25.45	10000	1.2652	0.6860	0.6552
0.1894	26.72	10500	1.2860	0.6790	0.6474
0.1757	27.99	11000	1.2892	0.6854	0.6541
0.1757	29.26	11500	1.3400	0.6803	0.6496
0.1599	30.53	12000	1.3630	0.6828	0.6493
0.1599	31.81	12500	1.3688	0.6854	0.6538
0.1531	33.08	13000	1.3962	0.6854	0.6534
0.1531	34.35	13500	1.4021	0.6841	0.6523
0.1452	35.62	14000	1.4029	0.6847	0.6524
0.1452	36.9	14500	1.4130	0.6886	0.6562
0.1391	38.17	15000	1.4203	0.6879	0.6553
0.1391	39.44	15500	1.4244	0.6873	0.6544

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
Created: May 23, 2023
Updated: May 23, 2023