TFG
Collection
Datasets and models leveraged and developed during my final degree work (TFG). Info and code can be found at https://github.com/enriquesaou/tfg-lm-qa
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18 items
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Updated
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2
flan-t5-small-mrqa
This model is a fine-tuned version of google/flan-t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7555
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: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 36
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.9984 | 416 | 0.8355 |
| 1.0359 | 1.9992 | 833 | 0.7848 |
| 0.8826 | 3.0 | 1250 | 0.7680 |
| 0.819 | 3.9984 | 1666 | 0.7622 |
| 0.7761 | 4.9992 | 2083 | 0.7541 |
| 0.77 | 6.0 | 2500 | 0.7569 |
| 0.77 | 6.9888 | 2912 | 0.7555 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Inference Providers
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Model tree for enriquesaou/flan-t5-small-mrqa
Base model
google/flan-t5-small