bert_sentiment_trainer – AI Model by Artanis1551 | AlphaNeural AI

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Artanis1551/
bert_sentiment_trainer

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text-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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bert_sentiment_trainer

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7044
Accuracy: 0.8857

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: 2.754984679344267e-05
train_batch_size: 16
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 3000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4787	0.32	250	0.4447	0.8338
0.374	0.64	500	0.3835	0.8613
0.3681	0.96	750	0.3533	0.8696
0.2456	1.28	1000	0.4425	0.8706
0.2092	1.6	1250	0.4393	0.8684
0.2827	1.92	1500	0.3814	0.8812
0.1424	2.24	1750	0.5589	0.8751
0.1791	2.56	2000	0.5869	0.8818
0.1297	2.88	2250	0.5741	0.8744
0.0474	3.21	2500	0.6328	0.8834
0.08	3.53	2750	0.7015	0.8748
0.088	3.85	3000	0.7044	0.8857

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0