This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the finer-139 dataset. It achieves the following results on the evaluation set:

Loss: 0.0882
Precision: 0.5339
Recall: 0.0360
F1: 0.0675
Accuracy: 0.9847

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0871	1.0	11255	0.0952	0.0	0.0	0.0	0.9843
0.0864	2.0	22510	0.0895	0.7640	0.0082	0.0162	0.9844
0.0929	3.0	33765	0.0882	0.5339	0.0360	0.0675	0.9847

Framework versions

Transformers 4.20.1
Pytorch 1.12.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1

muhtasham/bert-tiny-finetuned-finer

bertiny-finetuned-finer

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

muhtasham/
bert-tiny-finetuned-finer