---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
model-index:
- name: medication-lists
  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. -->

# medication-lists

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1027

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7961        | 0.3   | 50   | 0.7538          |
| 0.7207        | 0.61  | 100  | 0.3876          |
| 0.4596        | 0.91  | 150  | 0.2763          |
| 0.3536        | 1.22  | 200  | 0.2265          |
| 0.3089        | 1.52  | 250  | 0.1937          |
| 0.2736        | 1.83  | 300  | 0.1842          |
| 0.2415        | 2.13  | 350  | 0.1713          |
| 0.2309        | 2.44  | 400  | 0.1601          |
| 0.2011        | 2.74  | 450  | 0.1533          |
| 0.198         | 3.05  | 500  | 0.1464          |
| 0.1816        | 3.35  | 550  | 0.1418          |
| 0.1887        | 3.66  | 600  | 0.1354          |
| 0.1717        | 3.96  | 650  | 0.1295          |
| 0.1589        | 4.27  | 700  | 0.1320          |
| 0.1606        | 4.57  | 750  | 0.1230          |
| 0.1545        | 4.88  | 800  | 0.1255          |
| 0.1502        | 5.18  | 850  | 0.1247          |
| 0.1438        | 5.49  | 900  | 0.1251          |
| 0.1395        | 5.79  | 950  | 0.1222          |
| 0.1414        | 6.1   | 1000 | 0.1173          |
| 0.133         | 6.4   | 1050 | 0.1149          |
| 0.1338        | 6.71  | 1100 | 0.1124          |
| 0.1361        | 7.01  | 1150 | 0.1148          |
| 0.1269        | 7.32  | 1200 | 0.1137          |
| 0.123         | 7.62  | 1250 | 0.1145          |
| 0.1203        | 7.93  | 1300 | 0.1129          |
| 0.1194        | 8.23  | 1350 | 0.1081          |
| 0.1177        | 8.54  | 1400 | 0.1099          |
| 0.1173        | 8.84  | 1450 | 0.1109          |
| 0.113         | 9.15  | 1500 | 0.1107          |
| 0.1122        | 9.45  | 1550 | 0.1068          |
| 0.11          | 9.76  | 1600 | 0.1072          |
| 0.1078        | 10.06 | 1650 | 0.1086          |
| 0.101         | 10.37 | 1700 | 0.1088          |
| 0.1106        | 10.67 | 1750 | 0.1079          |
| 0.1094        | 10.98 | 1800 | 0.1109          |
| 0.1072        | 11.28 | 1850 | 0.1054          |
| 0.103         | 11.59 | 1900 | 0.1062          |
| 0.1009        | 11.89 | 1950 | 0.1051          |
| 0.1005        | 12.2  | 2000 | 0.1049          |
| 0.0985        | 12.5  | 2050 | 0.1059          |
| 0.0983        | 12.8  | 2100 | 0.1063          |
| 0.0953        | 13.11 | 2150 | 0.1062          |
| 0.0935        | 13.41 | 2200 | 0.1044          |
| 0.1003        | 13.72 | 2250 | 0.1034          |
| 0.0935        | 14.02 | 2300 | 0.1049          |
| 0.0935        | 14.33 | 2350 | 0.1038          |
| 0.096         | 14.63 | 2400 | 0.1020          |
| 0.0894        | 14.94 | 2450 | 0.1048          |
| 0.0931        | 15.24 | 2500 | 0.1034          |
| 0.0888        | 15.55 | 2550 | 0.1030          |
| 0.0904        | 15.85 | 2600 | 0.1038          |
| 0.0885        | 16.16 | 2650 | 0.1046          |
| 0.088         | 16.46 | 2700 | 0.1041          |
| 0.0925        | 16.77 | 2750 | 0.1027          |
| 0.0835        | 17.07 | 2800 | 0.1034          |
| 0.089         | 17.38 | 2850 | 0.1036          |
| 0.0844        | 17.68 | 2900 | 0.1043          |
| 0.0866        | 17.99 | 2950 | 0.1031          |
| 0.0835        | 18.29 | 3000 | 0.1030          |
| 0.0826        | 18.6  | 3050 | 0.1028          |
| 0.0874        | 18.9  | 3100 | 0.1018          |
| 0.0846        | 19.21 | 3150 | 0.1030          |
| 0.0852        | 19.51 | 3200 | 0.1026          |
| 0.0835        | 19.82 | 3250 | 0.1027          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.11.0
- Tokenizers 0.14.1