---
license: apache-2.0
base_model: google/t5-efficient-tiny
tags:
- generated_from_trainer
model-index:
- name: medication-single-t5-tiny
  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-single-t5-tiny

This model is a fine-tuned version of [google/t5-efficient-tiny](https://huggingface.co/google/t5-efficient-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0212

## 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: 0.004
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.321         | 0.08  | 100  | 0.6658          |
| 0.5928        | 0.16  | 200  | 0.3980          |
| 0.4394        | 0.23  | 300  | 0.2642          |
| 0.3582        | 0.31  | 400  | 0.2266          |
| 0.3174        | 0.39  | 500  | 0.1874          |
| 0.2776        | 0.47  | 600  | 0.1702          |
| 0.2286        | 0.55  | 700  | 0.1357          |
| 0.2052        | 0.63  | 800  | 0.1147          |
| 0.1962        | 0.7   | 900  | 0.0933          |
| 0.1641        | 0.78  | 1000 | 0.0771          |
| 0.1613        | 0.86  | 1100 | 0.0759          |
| 0.1482        | 0.94  | 1200 | 0.0677          |
| 0.1128        | 1.02  | 1300 | 0.0574          |
| 0.1139        | 1.09  | 1400 | 0.0509          |
| 0.1021        | 1.17  | 1500 | 0.0465          |
| 0.1013        | 1.25  | 1600 | 0.0449          |
| 0.0854        | 1.33  | 1700 | 0.0394          |
| 0.0839        | 1.41  | 1800 | 0.0375          |
| 0.0972        | 1.49  | 1900 | 0.0377          |
| 0.0775        | 1.56  | 2000 | 0.0352          |
| 0.0682        | 1.64  | 2100 | 0.0324          |
| 0.0676        | 1.72  | 2200 | 0.0310          |
| 0.0633        | 1.8   | 2300 | 0.0284          |
| 0.0608        | 1.88  | 2400 | 0.0279          |
| 0.0571        | 1.95  | 2500 | 0.0270          |
| 0.0557        | 2.03  | 2600 | 0.0259          |
| 0.0561        | 2.11  | 2700 | 0.0273          |
| 0.0542        | 2.19  | 2800 | 0.0247          |
| 0.0542        | 2.27  | 2900 | 0.0241          |
| 0.0514        | 2.35  | 3000 | 0.0248          |
| 0.0471        | 2.42  | 3100 | 0.0240          |
| 0.042         | 2.5   | 3200 | 0.0225          |
| 0.0547        | 2.58  | 3300 | 0.0221          |
| 0.0462        | 2.66  | 3400 | 0.0216          |
| 0.0444        | 2.74  | 3500 | 0.0216          |
| 0.0434        | 2.81  | 3600 | 0.0213          |
| 0.0374        | 2.89  | 3700 | 0.0213          |
| 0.0404        | 2.97  | 3800 | 0.0212          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.7
- Tokenizers 0.14.1