File size: 2,033 Bytes
354fe42
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- rouge
model-index:
- name: T5_finetuned
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: super_glue
      type: super_glue
      config: boolq
      split: train
      args: boolq
    metrics:
    - name: Rouge1
      type: rouge
      value: 79.3272
---

<!-- 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. -->

# T5_finetuned

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1077
- Rouge1: 79.3272
- Rouge2: 0.0
- Rougel: 79.2966
- Rougelsum: 79.3272
- Gen Len: 2.8269

## 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: 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 0.5134        | 1.0   | 590  | 0.1102          | 79.8165 | 0.0    | 79.8165 | 79.8471   | 2.7713  |
| 0.105         | 2.0   | 1180 | 0.1049          | 80.3364 | 0.0    | 80.3364 | 80.367    | 2.6483  |
| 0.1023        | 3.0   | 1770 | 0.1077          | 79.3272 | 0.0    | 79.2966 | 79.3272   | 2.8269  |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2