File size: 2,135 Bytes
64a8f4e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bdd38b4
 
 
 
 
 
 
64a8f4e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bdd38b4
 
 
 
 
64a8f4e
 
 
 
 
 
 
 
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-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-finetuned
  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-base-finetuned

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5109
- Rouge1: 84.3715
- Rouge2: 72.1078
- Rougel: 84.2884
- Rougelsum: 84.2975
- Gen Len: 14.2801
- Accuracy Log Reg: 0.7544

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len | Accuracy Log Reg |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:----------------:|
| 0.5683        | 1.0   | 2615  | 0.5281          | 84.0579 | 71.5636 | 83.9798 | 83.9904   | 14.2664 | 0.7474           |
| 0.5449        | 2.0   | 5230  | 0.5191          | 84.2078 | 71.7956 | 84.1207 | 84.1313   | 14.271  | 0.7496           |
| 0.5343        | 3.0   | 7845  | 0.5142          | 84.3083 | 72.002  | 84.228  | 84.2376   | 14.2794 | 0.753            |
| 0.5219        | 4.0   | 10460 | 0.5117          | 84.3502 | 72.0894 | 84.2692 | 84.2779   | 14.2845 | 0.7526           |
| 0.5179        | 5.0   | 13075 | 0.5109          | 84.3715 | 72.1078 | 84.2884 | 84.2975   | 14.2801 | 0.7544           |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1