metadata
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
results
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: 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