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---
license: mit
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: m2m100_418M-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize16-20epoch-1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus100
type: opus100
args: ar-en
metrics:
- name: Bleu
type: bleu
value: 13.1835
---
<!-- 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-2000instancesopus-leaningRate2e-05-batchSize16-20epoch-1
This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the opus100 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3640
- Bleu: 13.1835
- Meteor: 0.1189
- Gen Len: 17.72
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 6.1776 | 1.0 | 100 | 3.8904 | 10.5866 | 0.0995 | 16.64 |
| 2.4531 | 2.0 | 200 | 1.0928 | 12.3452 | 0.1108 | 17.0575 |
| 0.512 | 3.0 | 300 | 0.3625 | 10.5224 | 0.0982 | 17.2575 |
| 0.1924 | 4.0 | 400 | 0.3342 | 12.4242 | 0.1098 | 16.6325 |
| 0.1227 | 5.0 | 500 | 0.3403 | 13.0526 | 0.1185 | 17.3475 |
| 0.0889 | 6.0 | 600 | 0.3481 | 13.1323 | 0.1133 | 17.815 |
| 0.0651 | 7.0 | 700 | 0.3601 | 12.6684 | 0.1133 | 17.3525 |
| 0.0533 | 8.0 | 800 | 0.3640 | 13.1835 | 0.1189 | 17.72 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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