distilBERT_token_itr0_0.0001_essays_01_03_2022-15_18_35 – AI Model by ali2066 | AlphaNeural AI

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ali2066/
distilBERT_token_itr0_0.0001_essays_01_03_2022-15_18_35

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilBERT_token_itr0_0.0001_essays_01_03_2022-15_18_35

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: 0.1832
Precision: 0.6138
Recall: 0.7169
F1: 0.6613
Accuracy: 0.9332

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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	11	0.2740	0.4554	0.5460	0.4966	0.8943
No log	2.0	22	0.2189	0.5470	0.6558	0.5965	0.9193
No log	3.0	33	0.2039	0.5256	0.6706	0.5893	0.9198
No log	4.0	44	0.2097	0.5401	0.6795	0.6018	0.9237
No log	5.0	55	0.2255	0.6117	0.6825	0.6452	0.9223

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3