fine-tuned-DatasetQAS-IDK-MRC-with-indobert-large-p2-with-ITTL-with-freeze-LR-1e-05

This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.2708
• Exact Match: 52.7487
• F1: 60.8071

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: 4
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Exact Match	F1
6.4745	0.49	36	2.5724	35.6021	37.8405
3.5197	0.98	72	1.9912	28.0105	35.4278
2.1756	1.48	108	1.6669	35.7330	43.0612
2.1756	1.97	144	1.5047	39.3979	46.1664
1.6725	2.46	180	1.3222	45.9424	52.9355
1.336	2.95	216	1.3205	44.1099	51.6851
1.176	3.45	252	1.2526	47.5131	55.3298
1.176	3.94	288	1.2778	47.3822	54.7110
1.1089	4.44	324	1.2291	49.8691	57.2303
0.967	4.93	360	1.1944	52.4869	60.2202
0.967	5.42	396	1.2122	53.7958	61.3033
0.9202	5.91	432	1.2348	54.0576	61.6263
0.8719	6.41	468	1.2206	55.2356	62.9267
0.8205	6.9	504	1.2472	53.9267	61.6359
0.8205	7.4	540	1.2764	52.3560	60.2681
0.7907	7.89	576	1.2382	55.3665	63.0145
0.7533	8.38	612	1.2812	52.4869	60.4214
0.7533	8.87	648	1.2474	53.1414	60.6338
0.7345	9.37	684	1.2708	52.7487	60.8071

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu117
• Datasets 2.2.0
• Tokenizers 0.13.2