test-reward-model

This model is a fine-tuned version of w11wo/indonesian-roberta-base-sentiment-classifier on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2784
• Accuracy: 0.8817

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: 1e-05
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 12
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7179	0.67	50	0.6866	0.6237
0.6866	1.33	100	0.6661	0.7742
0.6546	2.0	150	0.6039	0.8280
0.5421	2.67	200	0.4624	0.8172
0.3965	3.33	250	0.3958	0.8280
0.3244	4.0	300	0.3502	0.8495
0.251	4.67	350	0.4012	0.8602
0.1579	5.33	400	0.3184	0.8602
0.135	6.0	450	0.3141	0.8710
0.1114	6.67	500	0.3474	0.8495
0.0929	7.33	550	0.2931	0.8495
0.0829	8.0	600	0.2757	0.8710
0.0834	8.67	650	0.2889	0.8817
0.057	9.33	700	0.2810	0.8925
0.0503	10.0	750	0.2800	0.8817
0.062	10.67	800	0.2806	0.8817
0.0303	11.33	850	0.2971	0.8817
0.0246	12.0	900	0.2784	0.8817

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.14.5
• Tokenizers 0.15.2