gec-flan-t5-large-stage-2

This model is a fine-tuned version of 512duncanl/gec-flan-t5-large on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1946
• F0.5: 0.6373
• Precision: 0.6715
• Recall: 0.5295

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: 4e-05
• train_batch_size: 24
• eval_batch_size: 24
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 8
• total_train_batch_size: 192
• 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
0.2415	1.0	193	0.2063	0.6416	0.6810	0.5209
0.1941	2.0	386	0.1946	0.6373	0.6715	0.5295

Framework versions

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