File size: 1,906 Bytes
b3d87ff
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5a1fd00
 
 
 
 
 
b3d87ff
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5a1fd00
b3d87ff
 
 
 
 
5a1fd00
 
 
 
b3d87ff
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-b8-10
  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-finetuned-b8-10

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: 3.6458
- Rouge1: 0.1334
- Rouge2: 0.1033
- Rougel: 0.1296
- Rougelsum: 0.1296
- Gen Len: 15.4277

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 5.1916        | 1.0   | 1357 | 3.8497          | 0.1095 | 0.086  | 0.1067 | 0.1064    | 12.6442 |
| 4.5138        | 2.0   | 2714 | 3.7329          | 0.1228 | 0.0959 | 0.1198 | 0.1195    | 14.4008 |
| 4.3429        | 3.0   | 4071 | 3.6736          | 0.1291 | 0.1    | 0.1255 | 0.1255    | 15.0502 |
| 4.3195        | 4.0   | 5428 | 3.6458          | 0.1334 | 0.1033 | 0.1296 | 0.1296    | 15.4277 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3