File size: 1,792 Bytes
e66f32d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
66bf475
e66f32d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: mit
base_model: facebook/mbart-large-50
tags:
- simplification
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart-en-translation
  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. -->

# mbart-en-translation

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on [watermelonhydro/es_en_2999 dataset](https://huggingface.co/datasets/watermelonhydro/es_en_2999).
It achieves the following results on the evaluation set:
- Loss: 1.2646
- Bleu: 51.3603
- Gen Len: 51.072

## 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: 5.6e-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 | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 282  | 1.0701          | 46.0434 | 49.7947 |
| 1.2218        | 2.0   | 564  | 0.9959          | 49.3118 | 50.584  |
| 1.2218        | 3.0   | 846  | 1.0847          | 50.359  | 51.352  |
| 0.311         | 4.0   | 1128 | 1.2012          | 50.6484 | 50.9733 |
| 0.311         | 5.0   | 1410 | 1.2646          | 51.3603 | 51.072  |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2