---
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: 0.1133

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6316        | 0.46  | 50   | 0.6287          |
| 0.6403        | 0.93  | 100  | 0.3378          |
| 0.4213        | 1.39  | 150  | 0.2460          |
| 0.3452        | 1.85  | 200  | 0.2184          |
| 0.306         | 2.31  | 250  | 0.1903          |
| 0.2634        | 2.78  | 300  | 0.1807          |
| 0.2423        | 3.24  | 350  | 0.1630          |
| 0.2224        | 3.7   | 400  | 0.1599          |
| 0.2107        | 4.17  | 450  | 0.1522          |
| 0.1922        | 4.63  | 500  | 0.1515          |
| 0.1887        | 5.09  | 550  | 0.1394          |
| 0.1821        | 5.56  | 600  | 0.1414          |
| 0.1705        | 6.02  | 650  | 0.1378          |
| 0.1602        | 6.48  | 700  | 0.1330          |
| 0.1579        | 6.94  | 750  | 0.1300          |
| 0.1497        | 7.41  | 800  | 0.1282          |
| 0.1534        | 7.87  | 850  | 0.1277          |
| 0.147         | 8.33  | 900  | 0.1274          |
| 0.1395        | 8.8   | 950  | 0.1204          |
| 0.1361        | 9.26  | 1000 | 0.1235          |
| 0.1353        | 9.72  | 1050 | 0.1210          |
| 0.1303        | 10.19 | 1100 | 0.1220          |
| 0.132         | 10.65 | 1150 | 0.1232          |
| 0.1262        | 11.11 | 1200 | 0.1193          |
| 0.1228        | 11.57 | 1250 | 0.1229          |
| 0.1261        | 12.04 | 1300 | 0.1215          |
| 0.1204        | 12.5  | 1350 | 0.1163          |
| 0.12          | 12.96 | 1400 | 0.1189          |
| 0.11          | 13.43 | 1450 | 0.1173          |
| 0.1183        | 13.89 | 1500 | 0.1149          |
| 0.108         | 14.35 | 1550 | 0.1178          |
| 0.1122        | 14.81 | 1600 | 0.1150          |
| 0.1126        | 15.28 | 1650 | 0.1157          |
| 0.112         | 15.74 | 1700 | 0.1152          |
| 0.1046        | 16.2  | 1750 | 0.1156          |
| 0.1057        | 16.67 | 1800 | 0.1138          |
| 0.1067        | 17.13 | 1850 | 0.1129          |
| 0.1078        | 17.59 | 1900 | 0.1140          |
| 0.1043        | 18.06 | 1950 | 0.1135          |
| 0.1033        | 18.52 | 2000 | 0.1138          |
| 0.1017        | 18.98 | 2050 | 0.1140          |
| 0.102         | 19.44 | 2100 | 0.1125          |
| 0.1012        | 19.91 | 2150 | 0.1133          |


### Framework versions

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