---
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: 0.0141

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 16.9156       | 1.08  | 100  | 4.0318          |
| 2.4758        | 2.15  | 200  | 0.2854          |
| 0.3554        | 3.23  | 300  | 0.0533          |
| 0.0788        | 4.3   | 400  | 0.0233          |
| 0.0377        | 5.38  | 500  | 0.0173          |
| 0.0254        | 6.45  | 600  | 0.0153          |
| 0.0205        | 7.53  | 700  | 0.0142          |
| 0.0158        | 8.6   | 800  | 0.0139          |
| 0.0148        | 9.68  | 900  | 0.0138          |
| 0.0135        | 10.75 | 1000 | 0.0138          |
| 0.0116        | 11.83 | 1100 | 0.0135          |
| 0.0121        | 12.9  | 1200 | 0.0135          |
| 0.0106        | 13.98 | 1300 | 0.0138          |
| 0.0097        | 15.05 | 1400 | 0.0136          |
| 0.0093        | 16.13 | 1500 | 0.0136          |
| 0.0094        | 17.2  | 1600 | 0.0139          |
| 0.0093        | 18.28 | 1700 | 0.0140          |
| 0.0097        | 19.35 | 1800 | 0.0141          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2