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
- Downloads last month
- -
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support