| --- |
| library_name: peft |
| license: apache-2.0 |
| base_model: google/flan-t5-base |
| tags: |
| - base_model:adapter:google/flan-t5-base |
| - lora |
| - transformers |
| metrics: |
| - rouge |
| model-index: |
| - name: Pakistan-Legal-ChatBot |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # Pakistan-Legal-ChatBot |
|
|
| This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: nan |
| - Rouge1: 0.2365 |
| - Rouge2: 0.0907 |
| - Rougel: 0.1905 |
| - Rougelsum: 0.1906 |
|
|
| ## 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: 0.0005 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | No log | 1.0 | 245 | nan | 0.2365 | 0.0907 | 0.1905 | 0.1906 | |
| | No log | 2.0 | 490 | nan | 0.2365 | 0.0907 | 0.1905 | 0.1906 | |
| | 0.0 | 3.0 | 735 | nan | 0.2365 | 0.0907 | 0.1905 | 0.1906 | |
| | 0.0 | 4.0 | 980 | nan | 0.2365 | 0.0907 | 0.1905 | 0.1906 | |
| | 0.0 | 5.0 | 1225 | nan | 0.2365 | 0.0907 | 0.1905 | 0.1906 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.18.0 |
| - Transformers 4.57.3 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
