flant5-finetuned-vilexnorm
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1309
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: 8
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.247 | 1.0 | 524 | 0.1982 |
0.2052 | 2.0 | 1048 | 0.1693 |
0.1769 | 3.0 | 1572 | 0.1540 |
0.1632 | 4.0 | 2096 | 0.1430 |
0.1568 | 5.0 | 2620 | 0.1368 |
0.1485 | 6.0 | 3144 | 0.1331 |
0.135 | 7.0 | 3668 | 0.1311 |
0.1283 | 8.0 | 4192 | 0.1309 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for funa21/flant5-finetuned-vilexnorm
Base model
google/flan-t5-base