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---
license: mit
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: m2m100_418M-evaluated-en-to-ar-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1
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: 41.8577
---
<!-- 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. -->
# m2m100_418M-evaluated-en-to-ar-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1
This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the un_multi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3603
- Bleu: 41.8577
- Meteor: 0.4199
- Gen Len: 41.9
## 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 5.111 | 0.5 | 100 | 3.2467 | 29.5017 | 0.3371 | 42.425 |
| 2.1491 | 1.0 | 200 | 1.0018 | 33.0563 | 0.3593 | 41.205 |
| 0.5911 | 1.5 | 300 | 0.4159 | 34.5818 | 0.3705 | 42.0625 |
| 0.3546 | 2.0 | 400 | 0.3723 | 36.6179 | 0.3823 | 40.925 |
| 0.2487 | 2.5 | 500 | 0.3595 | 39.0331 | 0.3956 | 41.56 |
| 0.2365 | 3.0 | 600 | 0.3485 | 39.5188 | 0.4023 | 41.6425 |
| 0.1687 | 3.5 | 700 | 0.3542 | 40.1728 | 0.4043 | 42.61 |
| 0.1791 | 4.0 | 800 | 0.3466 | 40.4858 | 0.4101 | 41.5575 |
| 0.1196 | 4.5 | 900 | 0.3493 | 41.2457 | 0.4123 | 41.755 |
| 0.1394 | 5.0 | 1000 | 0.3486 | 40.5606 | 0.4114 | 41.78 |
| 0.0958 | 5.5 | 1100 | 0.3568 | 41.1873 | 0.4157 | 41.7275 |
| 0.1043 | 6.0 | 1200 | 0.3557 | 41.2749 | 0.4165 | 41.935 |
| 0.073 | 6.5 | 1300 | 0.3603 | 41.8577 | 0.4199 | 41.9 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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