metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
base_model: roberta-base
model-index:
  - name: run-3
    results: []

run-3

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

Loss: 2.4223
Accuracy: 0.75
Precision: 0.7128
Recall: 0.6998
F1: 0.7043

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: 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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.0025	1.0	50	0.8925	0.63	0.6703	0.5704	0.5060
0.8187	2.0	100	0.7915	0.595	0.6007	0.5926	0.5344
0.5671	3.0	150	0.9573	0.695	0.6520	0.6350	0.6380
0.3218	4.0	200	0.9195	0.68	0.6447	0.6539	0.6461
0.2208	5.0	250	1.2429	0.715	0.6801	0.6617	0.6663
0.1614	6.0	300	1.5295	0.71	0.6736	0.6543	0.6423
0.1129	7.0	350	2.1055	0.71	0.6779	0.6413	0.6511
0.098	8.0	400	1.9579	0.705	0.6697	0.6558	0.6601
0.0479	9.0	450	2.0535	0.72	0.6794	0.6663	0.6711
0.0173	10.0	500	2.5381	0.7	0.6838	0.6604	0.6608
0.0308	11.0	550	2.4592	0.735	0.7014	0.6851	0.6901
0.0265	12.0	600	2.3131	0.725	0.6910	0.6845	0.6849
0.016	13.0	650	2.4025	0.74	0.7035	0.6915	0.6949
0.013	14.0	700	2.3933	0.745	0.7070	0.6831	0.6909
0.016	15.0	750	2.6819	0.725	0.7006	0.6738	0.6759
0.0126	16.0	800	2.3679	0.74	0.7050	0.6839	0.6898
0.0023	17.0	850	2.5252	0.745	0.7119	0.6880	0.6933
0.01	18.0	900	2.5598	0.74	0.7056	0.6828	0.6906
0.0093	19.0	950	2.4353	0.745	0.7057	0.6922	0.6974
0.0039	20.0	1000	2.4223	0.75	0.7128	0.6998	0.7043

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu116
Tokenizers 0.13.2