| --- |
| base_model: google/flan-t5-base |
| library_name: peft |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: results |
| results: [] |
| pipeline_tag: text2text-generation |
| --- |
| |
| <!-- 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.1507 |
|
|
| ## 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: 0.001 |
| - train_batch_size: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 3 |
| - total_train_batch_size: 12 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 16 |
| - training_steps: 1698 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 3.0084 | 0.59 | 50 | 2.5425 | |
| | 2.7308 | 1.18 | 100 | 2.4483 | |
| | 2.6435 | 1.76 | 150 | 2.3925 | |
| | 2.5873 | 2.35 | 200 | 2.3558 | |
| | 2.5247 | 2.94 | 250 | 2.3276 | |
| | 2.5323 | 3.53 | 300 | 2.3003 | |
| | 2.4288 | 4.12 | 350 | 2.2771 | |
| | 2.4247 | 4.71 | 400 | 2.2659 | |
| | 2.4014 | 5.29 | 450 | 2.2439 | |
| | 2.3761 | 5.88 | 500 | 2.2336 | |
| | 2.3056 | 6.47 | 550 | 2.2236 | |
| | 2.3443 | 7.06 | 600 | 2.2182 | |
| | 2.2877 | 7.65 | 650 | 2.2066 | |
| | 2.3028 | 8.24 | 700 | 2.1953 | |
| | 2.2589 | 8.82 | 750 | 2.1958 | |
| | 2.2306 | 9.41 | 800 | 2.1834 | |
| | 2.2571 | 10.0 | 850 | 2.1826 | |
| | 2.2109 | 10.59 | 900 | 2.1782 | |
| | 2.2216 | 11.18 | 950 | 2.1802 | |
| | 2.1881 | 11.76 | 1000 | 2.1734 | |
| | 2.1794 | 12.35 | 1050 | 2.1691 | |
| | 2.1933 | 12.94 | 1100 | 2.1654 | |
| | 2.134 | 13.53 | 1150 | 2.1682 | |
| | 2.1698 | 14.12 | 1200 | 2.1564 | |
| | 2.1477 | 14.71 | 1250 | 2.1599 | |
| | 2.1353 | 15.29 | 1300 | 2.1573 | |
| | 2.1206 | 15.88 | 1350 | 2.1525 | |
| | 2.1175 | 16.47 | 1400 | 2.1520 | |
| | 2.1142 | 17.06 | 1450 | 2.1531 | |
| | 2.1152 | 17.65 | 1500 | 2.1529 | |
| | 2.1073 | 18.24 | 1550 | 2.1529 | |
| | 2.099 | 18.82 | 1600 | 2.1520 | |
| | 2.1061 | 19.41 | 1650 | 2.1507 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.8.2 |
| - Transformers 4.38.1 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.2 |
