metadata

base_model: vinai/phobert-base
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: project-2-training-top
    results: []

project-2-training-top

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

Loss: 0.3248
F1: 0.5983
Roc Auc: 0.7277
Accuracy: 0.4931

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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.3401	1.0	73895	0.3248	0.5983	0.7277	0.4931

Framework versions

Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2