metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: criminal-case-classifier1
    results: []

criminal-case-classifier1

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: 1.8530
Accuracy: 0.5077

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 300

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9563	0.31	10	1.1314	0.3385
1.1275	0.62	20	1.0607	0.4769
1.0692	0.94	30	1.0871	0.2923
1.0717	1.25	40	1.1759	0.4154
1.0113	1.56	50	1.1322	0.3538
0.8463	1.88	60	1.1809	0.3846
0.8573	2.19	70	1.0676	0.4154
0.8711	2.5	80	1.0690	0.3846
0.809	2.81	90	1.1253	0.4154
0.7148	3.12	100	1.0913	0.4769
0.5847	3.44	110	1.0920	0.5077
0.5486	3.75	120	1.0597	0.5538
0.5184	4.06	130	1.1016	0.4769
0.2637	4.38	140	1.1908	0.4923
0.3562	4.69	150	1.0238	0.5385
0.3292	5.0	160	1.1011	0.5692
0.1333	5.31	170	1.3049	0.5385
0.1256	5.62	180	1.2819	0.5538
0.1415	5.94	190	1.4929	0.5231
0.0942	6.25	200	1.5290	0.5538
0.0548	6.56	210	1.4844	0.5538
0.0457	6.88	220	1.6174	0.5077
0.0226	7.19	230	1.6499	0.5538
0.032	7.5	240	1.7371	0.5077
0.0158	7.81	250	1.8099	0.5385
0.0244	8.12	260	1.9706	0.4769
0.0134	8.44	270	1.8825	0.5231
0.0117	8.75	280	1.8414	0.5077
0.0111	9.06	290	1.8478	0.5077
0.0107	9.38	300	1.8530	0.5077

Framework versions

Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2