metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: correct_distilBERT_token_itr0_1e-05_webDiscourse_01_03_2022-15_40_24
    results: []

correct_distilBERT_token_itr0_1e-05_webDiscourse_01_03_2022-15_40_24

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: 0.5794
Precision: 0.0094
Recall: 0.0147
F1: 0.0115
Accuracy: 0.7156

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	Precision	Recall	F1	Accuracy
No log	1.0	10	0.6319	0.08	0.0312	0.0449	0.6753
No log	2.0	20	0.6265	0.0364	0.0312	0.0336	0.6764
No log	3.0	30	0.6216	0.0351	0.0312	0.0331	0.6762
No log	4.0	40	0.6193	0.0274	0.0312	0.0292	0.6759
No log	5.0	50	0.6183	0.0222	0.0312	0.0260	0.6773

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3