metadata

license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased-finetuned-multiclass-classification
    results: []

distilbert-base-uncased-finetuned-multiclass-classification

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

Loss: 0.6039
Accuracy: 0.9045

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: 1.45e-05
train_batch_size: 4
eval_batch_size: 4
seed: 29
distributed_type: multi-GPU
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
2.6788	1.0	2638	2.1418	0.7233
1.289	2.0	5276	1.0718	0.8385
0.7581	3.0	7914	0.7530	0.8878
0.5557	4.0	10552	0.6371	0.9007
0.493	5.0	13190	0.6039	0.9045

Framework versions

Transformers 4.41.2
Pytorch 1.13.1+cpu
Datasets 2.13.1
Tokenizers 0.19.1