File size: 2,148 Bytes
0e5d7ce
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
048e123
0e5d7ce
c420252
 
 
 
 
 
0e5d7ce
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c420252
0e5d7ce
 
 
 
c420252
 
 
 
 
 
 
 
0e5d7ce
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-booksum
  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. -->

# t5-small-finetuned-booksum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an [booksum](https://huggingface.co/datasets/kmfoda/booksum) dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3115
- Rouge1: 20.5085
- Rouge2: 2.9908
- Rougel: 13.8508
- Rougelsum: 18.4822
- Gen Len: 228.1577

## 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:--------:|
| 3.7585        | 1.0   | 600  | 3.3969          | 17.6639 | 2.5697 | 12.3838 | 15.9802   | 307.0236 |
| 3.5518        | 2.0   | 1200 | 3.3526          | 20.0469 | 2.9053 | 13.6055 | 18.0492   | 248.2581 |
| 3.5108        | 3.0   | 1800 | 3.3318          | 20.0243 | 2.8879 | 13.5558 | 17.9889   | 245.3416 |
| 3.4798        | 4.0   | 2400 | 3.3202          | 20.1501 | 2.9346 | 13.6819 | 18.1977   | 232.3801 |
| 3.4542        | 5.0   | 3000 | 3.3134          | 20.6061 | 3.0311 | 13.9844 | 18.5832   | 217.8302 |
| 3.453         | 6.0   | 3600 | 3.3115          | 20.5085 | 2.9908 | 13.8508 | 18.4822   | 228.1577 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1