git-base-coco-dummy-temp100

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

• Loss: 0.3244
• Wer Score: 2.5274
• Blue Score: 0.1539

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
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Score	Blue Score
8.003	1.01	35	6.0344	1.2184	0.0042
4.5865	2.03	70	2.7898	2.0108	0.0150
1.6831	3.04	105	0.7239	1.8867	0.0250
0.5535	4.06	140	0.4567	1.9632	0.0377
0.3898	5.07	175	0.4016	2.2010	0.0618
0.3024	6.09	210	0.3712	1.7956	0.0892
0.2411	7.1	245	0.3506	2.5006	0.0950
0.2034	8.12	280	0.3388	2.1609	0.1094
0.1721	9.13	315	0.3319	2.2919	0.1092
0.1449	10.14	350	0.3236	2.1683	0.1184
0.1245	11.16	385	0.3205	2.3594	0.1242
0.1073	12.17	420	0.3160	2.4311	0.1343
0.0956	13.19	455	0.3141	2.3027	0.1327
0.0821	14.2	490	0.3121	2.3957	0.1369
0.07	15.22	525	0.3131	2.2508	0.1407
0.0678	16.23	560	0.3114	2.4291	0.1390
0.0563	17.25	595	0.3113	2.5218	0.1428
0.0518	18.26	630	0.3108	2.2964	0.1513
0.0474	19.28	665	0.3138	2.2457	0.1492
0.0407	20.29	700	0.3136	2.3072	0.1485
0.0383	21.3	735	0.3138	2.4791	0.1426
0.0373	22.32	770	0.3136	2.4541	0.1472
0.03	23.33	805	0.3145	2.4218	0.1500
0.0316	24.35	840	0.3141	2.4169	0.1466
0.0255	25.36	875	0.3149	2.5450	0.1473
0.0266	26.38	910	0.3159	2.4613	0.1475
0.0245	27.39	945	0.3161	2.4809	0.1506
0.0223	28.41	980	0.3172	2.4252	0.1516
0.0189	29.42	1015	0.3173	2.6111	0.1501
0.0204	30.43	1050	0.3184	2.5457	0.1518
0.0194	31.45	1085	0.3191	2.6389	0.1493
0.0154	32.46	1120	0.3188	2.5125	0.1518
0.017	33.48	1155	0.3192	2.5197	0.1485
0.0161	34.49	1190	0.3210	2.5103	0.1512
0.0146	35.51	1225	0.3206	2.4992	0.1527
0.0135	36.52	1260	0.3221	2.4620	0.1516
0.0139	37.54	1295	0.3216	2.4769	0.1519
0.0132	38.55	1330	0.3215	2.5613	0.1525
0.0121	39.57	1365	0.3222	2.5648	0.1518
0.0121	40.58	1400	0.3226	2.5601	0.1541
0.0114	41.59	1435	0.3231	2.4888	0.1527
0.0123	42.61	1470	0.3239	2.5037	0.1537
0.0101	43.62	1505	0.3241	2.5378	0.1526
0.0109	44.64	1540	0.3245	2.5312	0.1534
0.0109	45.65	1575	0.3245	2.5692	0.1529
0.0098	46.67	1610	0.3243	2.5583	0.1536
0.0109	47.68	1645	0.3248	2.5498	0.1536
0.0101	48.7	1680	0.3244	2.5274	0.1539

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.3
• Tokenizers 0.13.3