metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: finetuned_sentence_itr0_1e-05_all_01_03_2022-13_25_32
    results: []

finetuned_sentence_itr0_1e-05_all_01_03_2022-13_25_32

This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4787
Accuracy: 0.8138
F1: 0.8785
Precision: 0.8489
Recall: 0.9101

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
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	Accuracy	F1	Precision	Recall
No log	1.0	390	0.4335	0.7732	0.8533	0.8209	0.8883
0.5141	2.0	780	0.4196	0.8037	0.8721	0.8446	0.9015
0.3368	3.0	1170	0.4519	0.8098	0.8779	0.8386	0.9212
0.2677	4.0	1560	0.4787	0.8122	0.8785	0.8452	0.9146
0.2677	5.0	1950	0.4912	0.8146	0.8794	0.8510	0.9097

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3