File size: 1,723 Bytes
880b4df
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14ed422
 
 
 
880b4df
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14ed422
 
880b4df
 
14ed422
880b4df
 
 
 
 
 
 
 
14ed422
 
 
880b4df
 
 
 
 
14ed422
 
 
880b4df
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
---
base_model: facebook/nllb-200-distilled-600M
library_name: peft
license: cc-by-nc-4.0
metrics:
- bleu
- rouge
tags:
- generated_from_trainer
model-index:
- name: NLLB_DoRA
  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. -->

# NLLB_DoRA

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2708
- Bleu: 32.802
- Rouge: 0.6028
- Gen Len: 17.4444

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Rouge  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 1.3937        | 1.0   | 2000 | 1.3115          | 32.2196 | 0.5954 | 17.6569 |
| 1.3309        | 2.0   | 4000 | 1.2781          | 32.6752 | 0.6011 | 17.4931 |
| 1.3234        | 3.0   | 6000 | 1.2708          | 32.802  | 0.6028 | 17.4444 |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1