IOC – AI Model by wnkh | AlphaNeural AI

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wnkh/
IOC

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text2text-generation

generated_from_trainer

google/byt5-small

text-generation-inference

endpoints_compatible

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IOC

This model is a fine-tuned version of google/byt5-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3699
Cer: 0.1666
Cer Raw: 0.1865
Exact Match: 0.1572

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0003
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Cer	Cer Raw	Exact Match
0.3578	3.5487	20000	0.3699	0.1666	0.1865	0.1572

Framework versions

Transformers 4.57.6
Pytorch 2.10.0+cu128
Datasets 4.3.0
Tokenizers 0.22.2