File size: 2,050 Bytes
12972a2
 
 
 
 
e0f1ef5
 
12972a2
 
 
 
 
 
 
 
 
 
7a9cf68
e0f1ef5
 
 
12972a2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8b5dc25
 
12972a2
 
 
8b5dc25
12972a2
e0f1ef5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12972a2
 
 
 
7a9cf68
12972a2
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
---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task3-dataset1
  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. -->

# mt5-small-task3-dataset1

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3592
- Accuracy: 0.14

## 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: 5.6e-05
- 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
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6139        | 1.0   | 250  | 1.3916          | 0.102    |
| 1.5289        | 2.0   | 500  | 1.4550          | 0.108    |
| 1.4823        | 3.0   | 750  | 1.3630          | 0.132    |
| 1.4372        | 4.0   | 1000 | 1.3930          | 0.116    |
| 1.4563        | 5.0   | 1250 | 1.3857          | 0.124    |
| 1.4347        | 6.0   | 1500 | 1.3708          | 0.124    |
| 1.4303        | 7.0   | 1750 | 1.3856          | 0.136    |
| 1.4072        | 8.0   | 2000 | 1.3595          | 0.136    |
| 1.4045        | 9.0   | 2250 | 1.3677          | 0.13     |
| 1.3861        | 10.0  | 2500 | 1.3511          | 0.13     |
| 1.376         | 11.0  | 2750 | 1.3543          | 0.136    |
| 1.3699        | 12.0  | 3000 | 1.3592          | 0.14     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0