metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: my_Ws_extraction_model_27th_mar
    results: []

my_Ws_extraction_model_27th_mar

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

Loss: 0.2730
Precision: 0.4668
Recall: 0.4580
F1: 0.4623
Accuracy: 0.9046

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	76	0.2977	0.4502	0.4141	0.4314	0.8999
No log	2.0	152	0.2730	0.4668	0.4580	0.4623	0.9046

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu118
Datasets 2.17.0
Tokenizers 0.15.2