rob2rand_chen_w_prefix_tc

This model is a fine-tuned version of imamnurby/rob2rand_chen_w_prefix on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2749
• Bleu: 83.9120
• Em: 86.2159
• Bleu Em: 85.0639

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-06
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Em	Bleu Em
0.6922	0.71	500	0.2425	68.5819	79.7927	74.1873
0.086	1.42	1000	0.2480	70.9791	79.5855	75.2823
0.0865	2.13	1500	0.2567	68.7037	78.8256	73.7646
0.0758	2.84	2000	0.2483	69.4605	80.2418	74.8512
0.0683	3.55	2500	0.2662	68.3732	78.4456	73.4094
0.0643	4.26	3000	0.2700	66.5413	78.3765	72.4589
0.0596	4.97	3500	0.2611	67.4313	78.9637	73.1975
0.0519	5.68	4000	0.2697	68.3717	79.1019	73.7368
0.0478	6.39	4500	0.2914	69.7507	77.7202	73.7354
0.0461	7.1	5000	0.2776	68.5387	79.1019	73.8203
0.04	7.81	5500	0.2975	67.6316	78.1693	72.9004
0.0373	8.52	6000	0.2922	68.0161	79.4473	73.7317
0.0345	9.23	6500	0.3032	69.4580	79.2401	74.3490
0.032	9.94	7000	0.3104	67.2595	79.0328	73.1462
0.0294	10.65	7500	0.3077	65.8142	78.4801	72.1472
0.0269	11.36	8000	0.3092	70.2072	78.8601	74.5337
0.026	12.07	8500	0.3117	70.4504	79.4473	74.9489
0.0229	12.78	9000	0.3114	69.4635	79.2401	74.3518
0.0215	13.49	9500	0.3143	67.3601	79.3092	73.3346
0.0205	14.2	10000	0.3176	68.4031	78.9983	73.7007
0.0195	14.91	10500	0.3253	66.5673	78.9637	72.7655
0.0173	15.62	11000	0.3377	68.7553	78.7219	73.7386
0.0164	16.34	11500	0.3377	69.2474	79.1364	74.1919
0.0161	17.05	12000	0.3371	69.0846	79.6200	74.3523
0.0148	17.76	12500	0.3457	70.8330	79.3782	75.1056
0.0137	18.47	13000	0.3516	69.5576	79.2401	74.3988
0.0135	19.18	13500	0.3573	70.3232	79.1364	74.7298
0.0127	19.89	14000	0.3574	70.2481	79.1019	74.6750
0.0115	20.6	14500	0.3694	65.7587	78.3765	72.0676
0.0107	21.31	15000	0.3696	68.7923	78.5838	73.6880
0.0107	22.02	15500	0.3607	69.4452	78.8256	74.1354
0.0101	22.73	16000	0.3770	68.6731	78.5492	73.6112
0.0095	23.44	16500	0.3648	69.8402	79.7237	74.7819
0.0088	24.15	17000	0.3822	69.6238	79.0328	74.3283
0.0088	24.86	17500	0.3816	68.5422	79.1364	73.8393
0.0079	25.57	18000	0.3822	69.1359	79.2401	74.1880
0.0073	26.28	18500	0.3742	69.8331	79.6891	74.7611
0.007	26.99	19000	0.3849	69.5048	79.2746	74.3897
0.0072	27.7	19500	0.3881	69.6135	79.2055	74.4095
0.0059	28.41	20000	0.3922	70.2656	79.2746	74.7701
0.0069	29.12	20500	0.3936	68.2044	78.7910	73.4977
0.0059	29.83	21000	0.3983	69.6257	79.4473	74.5365
0.0055	30.54	21500	0.3973	70.4039	79.5509	74.9774
0.0057	31.25	22000	0.3960	70.3015	79.6546	74.9780
0.0056	31.96	22500	0.3945	69.9785	79.5855	74.7820
0.0049	32.67	23000	0.3947	70.1822	79.6546	74.9184
0.0049	33.38	23500	0.3957	69.1207	79.3437	74.2322
0.0048	34.09	24000	0.4097	68.8815	78.9292	73.9053
0.0043	34.8	24500	0.4039	70.0982	79.4473	74.7727
0.0044	35.51	25000	0.4080	69.3472	79.5164	74.4318
0.0042	36.22	25500	0.4066	69.0213	79.0674	74.0443
0.0038	36.93	26000	0.4128	69.1452	79.3092	74.2272
0.0037	37.64	26500	0.4134	69.2672	79.5164	74.3918
0.0034	38.35	27000	0.4161	69.7751	79.5509	74.6630
0.0038	39.06	27500	0.4037	69.4092	79.6546	74.5319
0.0031	39.77	28000	0.4041	69.3912	79.6546	74.5229
0.0032	40.48	28500	0.4185	69.1159	79.4473	74.2816
0.0031	41.19	29000	0.4245	68.6867	78.9983	73.8425
0.003	41.9	29500	0.4202	69.4091	79.3092	74.3591
0.0027	42.61	30000	0.4249	68.7400	79.0328	73.8864
0.0026	43.32	30500	0.4175	69.9729	79.8273	74.9001
0.0027	44.03	31000	0.4189	69.6688	79.5855	74.6271
0.0027	44.74	31500	0.4203	69.4071	79.5855	74.4963
0.0025	45.45	32000	0.4265	69.3197	79.1019	74.2108
0.0023	46.16	32500	0.4255	69.7513	79.3437	74.5475
0.0023	46.88	33000	0.4227	69.2893	79.5509	74.4201
0.0023	47.59	33500	0.4233	69.6060	79.5509	74.5785
0.002	48.3	34000	0.4239	69.0113	79.4819	74.2466
0.0024	49.01	34500	0.4239	68.9754	79.4128	74.1941
0.0019	49.72	35000	0.4228	68.9220	79.3782	74.1501

Framework versions

• Transformers 4.18.0
• Pytorch 1.7.1
• Datasets 2.1.0
• Tokenizers 0.12.1