gec-flan-t5-large

This model is a fine-tuned version of google/flan-t5-large on 512duncanl/c4_200m_cleaned_365k, a cleaned subset of Google's C4 200M. It achieves the following results on the evaluation set:

• Loss: 0.2685
• F0.5: 0.3635
• Precision: 0.3859
• Recall: 0.2950

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: 0.0001
• train_batch_size: 24
• eval_batch_size: 24
• seed: 42
• distributed_type: multi-GPU
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F0.5	Precision	Recall
0.3053	1.0	15000	0.2711	0.3514	0.3728	0.2856
0.2713	2.0	30000	0.2685	0.3635	0.3859	0.2950

Framework versions

• Transformers 4.53.2
• Pytorch 2.7.1+cu128
• Datasets 4.0.0
• Tokenizers 0.21.2