File size: 2,553 Bytes
5a24a5f |
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 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-4000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: un_multi
type: un_multi
args: ar-en
metrics:
- name: Bleu
type: bleu
value: 51.7715
---
<!-- 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. -->
# opus-mt-en-ar-evaluated-en-to-ar-4000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar) on the un_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1850
- Bleu: 51.7715
- Meteor: 0.5164
- Gen Len: 25.5612
## 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: 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: 11
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 0.6999 | 0.25 | 100 | 0.1959 | 50.1492 | 0.508 | 25.2788 |
| 0.1994 | 0.5 | 200 | 0.1931 | 51.003 | 0.513 | 25.4038 |
| 0.1863 | 0.75 | 300 | 0.1864 | 51.3268 | 0.5145 | 25.1675 |
| 0.1826 | 1.0 | 400 | 0.1841 | 51.2507 | 0.513 | 25.2388 |
| 0.1494 | 1.25 | 500 | 0.1840 | 51.4291 | 0.5159 | 25.4225 |
| 0.1483 | 1.5 | 600 | 0.1839 | 51.2645 | 0.5126 | 25.395 |
| 0.1547 | 1.75 | 700 | 0.1837 | 51.7589 | 0.5157 | 25.48 |
| 0.1487 | 2.0 | 800 | 0.1845 | 51.896 | 0.5177 | 25.3988 |
| 0.1235 | 2.25 | 900 | 0.1852 | 52.0583 | 0.5177 | 25.5212 |
| 0.1164 | 2.5 | 1000 | 0.1850 | 51.7715 | 0.5164 | 25.5612 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
|