token_final_tunned – AI Model by vinayak361 | AlphaNeural AI

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token_final_tunned

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token-classification

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token_final_tunned

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: 0.4670
Precision: 0.8269
Recall: 0.8442
F1: 0.8355
Accuracy: 0.8516

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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	108	0.7286	0.6581	0.7117	0.6838	0.7272
No log	2.0	216	0.5497	0.7529	0.7823	0.7673	0.8053
No log	3.0	324	0.4884	0.7911	0.8145	0.8026	0.8277
No log	4.0	432	0.4723	0.8144	0.8278	0.8210	0.8408
0.6038	5.0	540	0.4597	0.8032	0.8315	0.8171	0.8428
0.6038	6.0	648	0.4583	0.8208	0.8322	0.8264	0.8480
0.6038	7.0	756	0.4641	0.8290	0.8442	0.8365	0.8520
0.6038	8.0	864	0.4670	0.8269	0.8442	0.8355	0.8516

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu102
Datasets 2.2.2
Tokenizers 0.12.1