Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.4	100	1.3257	0.6259	0.2897	0.3961	0.6677
No log	0.8	200	0.8512	0.6479	0.5297	0.5829	0.7870
No log	1.2	300	0.6603	0.7311	0.6472	0.6866	0.8302
No log	1.6	400	0.5604	0.7580	0.7144	0.7355	0.8515
1.0344	2.0	500	0.4834	0.7920	0.7515	0.7712	0.8711
1.0344	2.4	600	0.4352	0.8070	0.7792	0.7929	0.8812
1.0344	2.8	700	0.4045	0.8146	0.8149	0.8148	0.8925
1.0344	3.2	800	0.4051	0.8067	0.8208	0.8137	0.8897
1.0344	3.6	900	0.3774	0.8211	0.8328	0.8269	0.8977
0.3942	4.0	1000	0.3556	0.8355	0.8340	0.8347	0.9025
0.3942	4.4	1100	0.3703	0.8211	0.8496	0.8351	0.9001
0.3942	4.8	1200	0.3430	0.8367	0.8486	0.8426	0.9057
0.3942	5.2	1300	0.3492	0.8349	0.8469	0.8409	0.9051
0.3942	5.6	1400	0.3259	0.8551	0.8498	0.8525	0.9108
0.2561	6.0	1500	0.3276	0.8422	0.8610	0.8515	0.9113
0.2561	6.4	1600	0.3307	0.8546	0.8497	0.8522	0.9110
0.2561	6.8	1700	0.3180	0.8527	0.8559	0.8543	0.9136
0.2561	7.2	1800	0.3239	0.8525	0.8593	0.8559	0.9135
0.2561	7.6	1900	0.3322	0.8499	0.8703	0.8600	0.9145
0.1866	8.0	2000	0.3265	0.8465	0.8681	0.8572	0.9131
0.1866	8.4	2100	0.3248	0.8588	0.8618	0.8603	0.9170
0.1866	8.8	2200	0.3269	0.8579	0.8629	0.8604	0.9162
0.1866	9.2	2300	0.3273	0.8656	0.8663	0.8660	0.9195
0.1866	9.6	2400	0.3312	0.8593	0.8702	0.8647	0.9187
0.1439	10.0	2500	0.3200	0.8639	0.8703	0.8671	0.9209
0.1439	10.4	2600	0.3367	0.8540	0.8761	0.8649	0.9183
0.1439	10.8	2700	0.3370	0.8614	0.8699	0.8656	0.9191
0.1439	11.2	2800	0.3294	0.8735	0.8690	0.8712	0.9221
0.1439	11.6	2900	0.3405	0.8653	0.8734	0.8693	0.9205
0.1186	12.0	3000	0.3334	0.8629	0.8767	0.8697	0.9210
0.1186	12.4	3100	0.3376	0.8653	0.8747	0.8700	0.9218
0.1186	12.8	3200	0.3362	0.8663	0.8752	0.8707	0.9209
0.1186	13.2	3300	0.3317	0.8729	0.8719	0.8724	0.9225
0.1186	13.6	3400	0.3408	0.8706	0.8714	0.8710	0.9213
0.0997	14.0	3500	0.3399	0.8693	0.8761	0.8727	0.9225
0.0997	14.4	3600	0.3445	0.8623	0.8767	0.8694	0.9208
0.0997	14.8	3700	0.3403	0.8673	0.8775	0.8724	0.9225
0.0997	15.2	3800	0.3492	0.8652	0.8763	0.8707	0.9209
0.0997	15.6	3900	0.3442	0.8692	0.8760	0.8726	0.9228
0.0891	16.0	4000	0.3441	0.8672	0.8767	0.8719	0.9225

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

kaydee/layoutlmv3-wildreceipt

layoutlmv3-wildreceipt

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

kaydee/
layoutlmv3-wildreceipt