metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
  - precision
  - recall
model-index:
  - name: bert-bert-cased-first512-Conflict-SEP
    results: []

bert-bert-cased-first512-Conflict-SEP

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

Loss: 0.6806
F1: 0.6088
Accuracy: 0.5914
Precision: 0.5839
Recall: 0.6360

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: 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy	Precision	Recall
0.7027	1.0	685	0.6956	0.6018	0.5365	0.5275	0.7003
0.7009	2.0	1370	0.6986	0.6667	0.5	0.5	1.0
0.7052	3.0	2055	0.6983	0.6667	0.5	0.5	1.0
0.6987	4.0	2740	0.6830	0.5235	0.5636	0.5764	0.4795
0.6761	5.0	3425	0.6806	0.6088	0.5914	0.5839	0.6360

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.1.0
Tokenizers 0.12.1