File size: 2,574 Bytes
fc527eb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7d218d5
fc527eb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7d218d5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fc527eb
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
---
license: apache-2.0
base_model: google/t5-efficient-small
tags:
- generated_from_trainer
model-index:
- name: medication-single-t5
  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

This model is a fine-tuned version of [google/t5-efficient-small](https://huggingface.co/google/t5-efficient-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0134

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5257        | 0.08  | 100  | 0.2084          |
| 0.1412        | 0.16  | 200  | 0.0880          |
| 0.0902        | 0.23  | 300  | 0.0543          |
| 0.0791        | 0.31  | 400  | 0.0456          |
| 0.072         | 0.39  | 500  | 0.0392          |
| 0.0567        | 0.47  | 600  | 0.0349          |
| 0.0507        | 0.55  | 700  | 0.0312          |
| 0.0493        | 0.63  | 800  | 0.0285          |
| 0.041         | 0.7   | 900  | 0.0246          |
| 0.0423        | 0.78  | 1000 | 0.0255          |
| 0.0382        | 0.86  | 1100 | 0.0247          |
| 0.0375        | 0.94  | 1200 | 0.0217          |
| 0.0298        | 1.02  | 1300 | 0.0211          |
| 0.0327        | 1.09  | 1400 | 0.0198          |
| 0.0272        | 1.17  | 1500 | 0.0195          |
| 0.0301        | 1.25  | 1600 | 0.0183          |
| 0.0259        | 1.33  | 1700 | 0.0179          |
| 0.0273        | 1.41  | 1800 | 0.0164          |
| 0.0244        | 1.49  | 1900 | 0.0163          |
| 0.0222        | 1.56  | 2000 | 0.0161          |
| 0.0214        | 1.64  | 2100 | 0.0158          |
| 0.0199        | 1.72  | 2200 | 0.0146          |
| 0.0202        | 1.8   | 2300 | 0.0141          |
| 0.0214        | 1.88  | 2400 | 0.0135          |
| 0.018         | 1.95  | 2500 | 0.0134          |


### Framework versions

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