File size: 2,853 Bytes
3dd82eb
 
 
 
 
 
1aba744
3dd82eb
 
 
 
 
 
 
 
 
 
012f990
3dd82eb
012f990
 
 
 
 
3dd82eb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1aba744
 
3dd82eb
 
 
e47a42a
3dd82eb
 
 
e47a42a
 
012f990
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3dd82eb
 
 
 
 
1aba744
3dd82eb
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
---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mt5-small-task3-dataset2
  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-dataset2

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5208
- Accuracy: 0.06
- Mse: 4.0312
- Log-distance: 0.6188
- S Score: 0.5264

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse    | Log-distance | S Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
| 10.5119       | 1.0   | 250  | 2.2161          | 0.016    | 4.4296 | 0.7765       | 0.4528  |
| 3.0365        | 2.0   | 500  | 1.7090          | 0.026    | 4.5503 | 0.7910       | 0.4512  |
| 2.2209        | 3.0   | 750  | 1.6007          | 0.052    | 4.7537 | 0.6721       | 0.4932  |
| 1.9292        | 4.0   | 1000 | 1.5895          | 0.042    | 4.1466 | 0.6578       | 0.5020  |
| 1.7982        | 5.0   | 1250 | 1.5695          | 0.052    | 4.7583 | 0.6732       | 0.4928  |
| 1.7379        | 6.0   | 1500 | 1.5367          | 0.046    | 4.2149 | 0.6615       | 0.5000  |
| 1.7081        | 7.0   | 1750 | 1.5376          | 0.054    | 4.1174 | 0.6606       | 0.5028  |
| 1.6768        | 8.0   | 2000 | 1.5462          | 0.054    | 4.1031 | 0.6584       | 0.5032  |
| 1.6515        | 9.0   | 2250 | 1.5256          | 0.052    | 4.1256 | 0.6525       | 0.5076  |
| 1.6235        | 10.0  | 2500 | 1.5512          | 0.052    | 4.1063 | 0.6542       | 0.5040  |
| 1.6289        | 11.0  | 2750 | 1.5346          | 0.06     | 4.1069 | 0.6390       | 0.5140  |
| 1.6077        | 12.0  | 3000 | 1.5385          | 0.058    | 4.0832 | 0.6298       | 0.5200  |
| 1.6014        | 13.0  | 3250 | 1.5204          | 0.058    | 3.9666 | 0.6236       | 0.5240  |
| 1.5998        | 14.0  | 3500 | 1.5201          | 0.06     | 4.0911 | 0.6142       | 0.5304  |
| 1.5994        | 15.0  | 3750 | 1.5208          | 0.06     | 4.0312 | 0.6188       | 0.5264  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0