Image_Captioner_Mimic

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

• Loss: 0.0963
• Rouge1: 32.528
• Rouge2: 19.9922
• Rougel: 31.403
• Rougelsum: 31.9372
• Gen Len: 12.5584

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
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.0597	1.0	24457	0.0567	37.8657	27.8087	37.4596	37.752	9.9527
0.0533	2.0	48914	0.0526	39.2211	28.2036	38.5786	38.9976	10.7079
0.0507	3.0	73371	0.0499	39.3449	28.3875	38.7151	39.0449	10.2091
0.0457	4.0	97828	0.0479	39.8753	28.5	39.127	39.6178	11.2407
0.0419	5.0	122285	0.0461	40.0478	28.797	39.3201	39.7468	10.3153
0.0406	6.0	146742	0.0445	39.7923	28.4281	39.0583	39.4523	10.4186
0.0373	7.0	171199	0.0429	39.954	28.535	39.2226	39.6457	10.6640
0.0347	8.0	195656	0.0419	39.4329	28.0336	38.6815	39.0968	10.7775
0.031	9.0	220113	0.0411	39.4524	28.1057	38.6998	39.0906	10.8397
0.0286	10.0	244570	0.0407	39.1493	27.639	38.3784	38.8085	10.9530
0.0261	11.0	269027	0.0408	38.8083	27.2206	37.9679	38.422	11.2390
0.0249	12.0	293484	0.0412	38.3972	26.7316	37.5838	38.0409	11.4510
0.0214	13.0	317941	0.0424	37.785	26.3302	36.9553	37.3764	11.4482
0.0188	14.0	342398	0.0438	36.9552	25.3108	36.0278	36.4965	11.6232
0.0174	15.0	366855	0.0458	35.6476	23.9574	34.6526	35.1259	11.6605
0.0153	16.0	391312	0.0487	34.657	22.8337	33.5891	34.1343	12.2395
0.013	17.0	415769	0.0518	33.5548	21.1569	32.4899	33.0394	12.2604
0.0114	18.0	440226	0.0559	34.3809	22.0108	33.2698	33.8578	12.0861
0.01	19.0	464683	0.0601	32.9062	20.3145	31.8147	32.3802	12.5176
0.0081	20.0	489140	0.0651	32.9482	20.3862	31.865	32.3837	12.4577
0.0069	21.0	513597	0.0698	32.3054	19.764	31.2178	31.7592	12.4939
0.0057	22.0	538054	0.0751	31.7627	19.0106	30.6263	31.175	12.7530
0.0048	23.0	562511	0.0793	31.8295	19.255	30.6958	31.2314	12.6077
0.0041	24.0	586968	0.0834	32.1523	19.2017	30.9774	31.5383	12.7461
0.0032	25.0	611425	0.0870	32.5379	20.0041	31.3903	31.9037	12.6848
0.0025	26.0	635882	0.0903	32.6757	20.1388	31.5495	32.0827	12.5950
0.0023	27.0	660339	0.0927	32.0874	19.3546	30.9125	31.4675	12.6290
0.0019	28.0	684796	0.0947	32.6988	20.1847	31.5643	32.1143	12.5412
0.0017	29.0	709253	0.0958	32.4574	19.7702	31.2955	31.8608	12.5558
0.0014	30.0	733710	0.0963	32.528	19.9922	31.403	31.9372	12.5584

Framework versions

• Transformers 4.37.1
• Pytorch 1.13.1+cu117
• Datasets 2.15.0
• Tokenizers 0.15.1