File size: 1,975 Bytes
f151f60
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-samsum-acsi-ami
  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. -->

# bart-large-cnn-samsum-acsi-ami

This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/philschmid/bart-large-cnn-samsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1361
- Rouge1: 39.7563
- Rouge2: 11.1286
- Rougel: 23.2632
- Rougelsum: 36.5664
- Gen Len: 108.15

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 20   | 3.2095          | 39.8174 | 11.5559 | 24.0296 | 36.3048   | 108.5   |
| No log        | 2.0   | 40   | 3.1361          | 39.7563 | 11.1286 | 23.2632 | 36.5664   | 108.15  |
| No log        | 3.0   | 60   | 3.1599          | 41.79   | 12.0967 | 23.5336 | 37.6859   | 122.95  |
| No log        | 4.0   | 80   | 3.2878          | 42.3161 | 12.2801 | 23.9352 | 38.2391   | 122.7   |
| No log        | 5.0   | 100  | 3.3671          | 40.7968 | 10.7336 | 22.9434 | 36.4383   | 129.225 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2