trocr-base-handwritten

Eddy-Emmanuel/trocr-base-handwritten

trocr-base-handwritten is a machine learning model from Eddy-Emmanuel. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

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At a glance

Library: peft
License: mit
Access: Public
Created: Aug 8, 2026
Updated: Aug 8, 2026
SHA: 6be86e17

Base models

microsoft/trocr-base-handwritten

Model card

From the Hugging Face model README

trocr-base-handwritten

This model is a fine-tuned version of microsoft/trocr-base-handwritten on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.4825
Cer: 0.1647
Wer: 0.3687
Penalized Wer: 0.3822
Combined: 0.2735

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: 32
eval_batch_size: 32
seed: 2026
optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.05
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer	Wer	Penalized Wer	Combined
8.3684	1.0	116	7.7234	0.5314	0.8450	0.8862	0.7088
6.1191	2.0	232	4.0425	0.4222	0.7276	0.7603	0.5912
3.5055	3.0	348	3.0009	0.3198	0.6157	0.6434	0.4816
2.7962	4.0	464	2.6273	0.2876	0.5739	0.6002	0.4439
2.5346	5.0	580	2.4117	0.2671	0.5368	0.5581	0.4126
2.3641	6.0	696	2.2578	0.2518	0.5180	0.5396	0.3957
2.2352	7.0	812	2.1378	0.2388	0.4889	0.5075	0.3731
2.1021	8.0	928	2.0344	0.2263	0.4705	0.4882	0.3572
1.9916	9.0	1044	1.9547	0.2186	0.4551	0.4724	0.3455
1.8868	10.0	1160	1.8899	0.2096	0.4447	0.4627	0.3362
1.8350	11.0	1276	1.8264	0.2030	0.4330	0.4504	0.3267
1.7901	12.0	1392	1.7776	0.1966	0.4228	0.4386	0.3176
1.7575	13.0	1508	1.7373	0.1918	0.4122	0.4282	0.3100
1.6409	14.0	1624	1.6968	0.1866	0.4094	0.4261	0.3064
1.6370	15.0	1740	1.6660	0.1835	0.4066	0.4223	0.3029
1.5953	16.0	1856	1.6408	0.1806	0.4003	0.4156	0.2981
1.5737	17.0	1972	1.6150	0.1787	0.3960	0.4111	0.2949
1.5381	18.0	2088	1.5917	0.1768	0.3925	0.4078	0.2923
1.5058	19.0	2204	1.5737	0.1740	0.3840	0.3977	0.2859
1.4760	20.0	2320	1.5564	0.1707	0.3819	0.3954	0.2831
1.4345	21.0	2436	1.5408	0.1718	0.3786	0.3924	0.2821
1.4309	22.0	2552	1.5288	0.1694	0.3793	0.3930	0.2812
1.4147	23.0	2668	1.5168	0.1681	0.3773	0.3922	0.2801
1.3955	24.0	2784	1.5072	0.1686	0.3743	0.3885	0.2785
1.4017	25.0	2900	1.5017	0.1661	0.3736	0.3876	0.2769
1.4114	26.0	3016	1.4926	0.1658	0.3708	0.3847	0.2753
1.4293	27.0	3132	1.4886	0.1639	0.3702	0.3838	0.2738
1.3707	28.0	3248	1.4852	0.1657	0.3713	0.3850	0.2753
1.3794	29.0	3364	1.4832	0.1638	0.3663	0.3797	0.2718
1.3586	30.0	3480	1.4825	0.1647	0.3687	0.3822	0.2735

Framework versions

PEFT 0.19.1
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2

Library: peft
License: mit
Created: Aug 8, 2026
Updated: Aug 8, 2026