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lim-gec – AI Model by angelafearn | AlphaNeural AI
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angelafearn
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lim-gec
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transformers
safetensors
t5
text2text-generation
generated_from_trainer
gotutiyan/gec-t5-large-clang8
finetune
cc-by-nc-sa-4.0
text-generation-inference
endpoints_compatible
us
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lim-gec
This model is a fine-tuned version of
gotutiyan/gec-t5-large-clang8
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0217
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: 0.0003
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
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
lr_scheduler_warmup_steps: 500
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
0.4193
0.1348
500
0.0352
0.3001
0.2697
1000
0.0286
0.2633
0.4045
1500
0.0260
0.2293
0.5394
2000
0.0246
0.2215
0.6742
2500
0.0236
0.2161
0.8090
3000
0.0221
0.2158
0.9439
3500
0.0217
Framework versions
Transformers 5.2.0
Pytorch 2.7.0+cu126
Datasets 4.6.1
Tokenizers 0.22.2
