metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
  - recall
  - precision
model-index:
  - name: distil_bert_tuned_2
    results: []

distil_bert_tuned_2

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

Loss: 0.5698
F1: 0.8253
Accuracy: 0.7816
Recall: 0.7088
Precision: 0.2347

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy	Recall	Precision
0.5698	1.0	605	0.5390	0.8419	0.8063	0.6549	0.2502
0.5006	2.0	1210	0.5075	0.8052	0.7527	0.7599	0.2192
0.4526	3.0	1815	0.5698	0.8253	0.7816	0.7088	0.2347

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cpu
Datasets 2.14.5
Tokenizers 0.13.3