bert-base-uncased-yelp_polarity

This model is a fine-tuned version of bert-base-uncased on the yelp_polarity dataset. It achieves the following results on the evaluation set:

• Loss: 0.3222
• Accuracy: 0.9516

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: 5e-05
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 277200
• training_steps: 2772000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8067	0.0	2000	0.8241	0.4975
0.5482	0.01	4000	0.3507	0.8591
0.3427	0.01	6000	0.3750	0.9139
0.4133	0.01	8000	0.5520	0.9016
0.4301	0.02	10000	0.3803	0.9304
0.3716	0.02	12000	0.4168	0.9337
0.4076	0.03	14000	0.5042	0.9170
0.3674	0.03	16000	0.4806	0.9268
0.3813	0.03	18000	0.4227	0.9261
0.3723	0.04	20000	0.3360	0.9418
0.3876	0.04	22000	0.3255	0.9407
0.3351	0.04	24000	0.3283	0.9404
0.34	0.05	26000	0.3489	0.9430
0.3006	0.05	28000	0.3302	0.9464
0.349	0.05	30000	0.3853	0.9375
0.3696	0.06	32000	0.2992	0.9454
0.3301	0.06	34000	0.3484	0.9464
0.3151	0.06	36000	0.3529	0.9455
0.3682	0.07	38000	0.3052	0.9420
0.3184	0.07	40000	0.3323	0.9466
0.3207	0.08	42000	0.3133	0.9532
0.3346	0.08	44000	0.3826	0.9414
0.3008	0.08	46000	0.3059	0.9484
0.3306	0.09	48000	0.3089	0.9475
0.342	0.09	50000	0.3611	0.9486
0.3424	0.09	52000	0.3227	0.9445
0.3044	0.1	54000	0.3130	0.9489
0.3278	0.1	56000	0.3827	0.9368
0.288	0.1	58000	0.3080	0.9504
0.3342	0.11	60000	0.3252	0.9471
0.3737	0.11	62000	0.4250	0.9343

Framework versions

• Transformers 4.10.2
• Pytorch 1.7.1
• Datasets 1.6.1
• Tokenizers 0.10.3