|
--- |
|
license: apache-2.0 |
|
base_model: google/flan-t5-base |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: ingredient_prune |
|
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. --> |
|
|
|
# ingredient_prune |
|
|
|
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: 0.3196 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 40.04 | 0.18 | 10 | 30.2044 | |
|
| 28.2106 | 0.36 | 20 | 22.6394 | |
|
| 22.4239 | 0.55 | 30 | 16.8570 | |
|
| 17.149 | 0.73 | 40 | 10.1178 | |
|
| 11.379 | 0.91 | 50 | 5.1010 | |
|
| 6.6773 | 1.09 | 60 | 4.7149 | |
|
| 5.0559 | 1.27 | 70 | 4.4758 | |
|
| 4.6474 | 1.45 | 80 | 4.2656 | |
|
| 4.3934 | 1.64 | 90 | 3.9831 | |
|
| 4.1421 | 1.82 | 100 | 3.6196 | |
|
| 3.9066 | 2.0 | 110 | 3.0985 | |
|
| 3.5465 | 2.18 | 120 | 2.4730 | |
|
| 3.1722 | 2.36 | 130 | 1.8153 | |
|
| 2.8787 | 2.55 | 140 | 1.5002 | |
|
| 2.564 | 2.73 | 150 | 1.1748 | |
|
| 2.296 | 2.91 | 160 | 0.9380 | |
|
| 2.135 | 3.09 | 170 | 0.7860 | |
|
| 1.9049 | 3.27 | 180 | 0.6740 | |
|
| 1.7388 | 3.45 | 190 | 0.5633 | |
|
| 1.5868 | 3.64 | 200 | 0.4853 | |
|
| 1.5128 | 3.82 | 210 | 0.4449 | |
|
| 1.3889 | 4.0 | 220 | 0.4066 | |
|
| 1.3273 | 4.18 | 230 | 0.3800 | |
|
| 1.2965 | 4.36 | 240 | 0.3589 | |
|
| 1.1939 | 4.55 | 250 | 0.3389 | |
|
| 1.2203 | 4.73 | 260 | 0.3254 | |
|
| 1.1422 | 4.91 | 270 | 0.3196 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.15.2 |
|
|
