distilbert-base-uncased-english-cefr-lexical-evaluation-dt-v4 – AI Model by hafidikhsan | AlphaNeural AI

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hafidikhsan/
distilbert-base-uncased-english-cefr-lexical-evaluation-dt-v4

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-english-cefr-lexical-evaluation-dt-v4

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: 0.5788
Accuracy: 0.8580
F1: 0.8573
Precision: 0.8576
Recall: 0.8580

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: 0.0001
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_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.6508	1.0	3527	0.6211	0.7680	0.7675	0.7789	0.7680
0.4088	2.0	7054	0.4281	0.8562	0.8549	0.8574	0.8562
0.2476	3.0	10581	0.4526	0.8577	0.8570	0.8574	0.8577
0.1298	4.0	14108	0.5618	0.8638	0.8630	0.8635	0.8638
0.0615	5.0	17635	0.6939	0.8632	0.8629	0.8629	0.8632

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3