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# opus-mt-ar-en-finetuned-ar-to-en

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the opus_infopankki dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7636
- Bleu: 53.5086
- Gen Len: 13.5728

## 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-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 278  | 1.5114          | 35.2767 | 14.2084 |
| 1.6677        | 2.0   | 556  | 1.4025          | 37.5243 | 14.0245 |
| 1.6677        | 3.0   | 834  | 1.3223          | 39.4262 | 13.8101 |
| 1.4743        | 4.0   | 1112 | 1.2567          | 40.7045 | 13.8533 |
| 1.4743        | 5.0   | 1390 | 1.2001          | 41.8356 | 13.8083 |
| 1.3428        | 6.0   | 1668 | 1.1504          | 43.2448 | 13.6958 |
| 1.3428        | 7.0   | 1946 | 1.1072          | 44.177  | 13.6783 |
| 1.2595        | 8.0   | 2224 | 1.0701          | 45.17   | 13.6587 |
| 1.1829        | 9.0   | 2502 | 1.0345          | 45.9612 | 13.6706 |
| 1.1829        | 10.0  | 2780 | 1.0042          | 46.9009 | 13.6236 |
| 1.1188        | 11.0  | 3058 | 0.9760          | 47.7478 | 13.6205 |
| 1.1188        | 12.0  | 3336 | 0.9505          | 48.3082 | 13.6283 |
| 1.0735        | 13.0  | 3614 | 0.9270          | 48.9782 | 13.6203 |
| 1.0735        | 14.0  | 3892 | 0.9060          | 49.5541 | 13.6311 |
| 1.0269        | 15.0  | 4170 | 0.8869          | 49.9905 | 13.6222 |
| 1.0269        | 16.0  | 4448 | 0.8700          | 50.4806 | 13.6047 |
| 0.9983        | 17.0  | 4726 | 0.8538          | 50.9186 | 13.6159 |
| 0.9647        | 18.0  | 5004 | 0.8398          | 51.3492 | 13.6146 |
| 0.9647        | 19.0  | 5282 | 0.8271          | 51.7219 | 13.5275 |
| 0.9398        | 20.0  | 5560 | 0.8156          | 52.0177 | 13.5756 |
| 0.9398        | 21.0  | 5838 | 0.8053          | 52.3619 | 13.5807 |
| 0.9206        | 22.0  | 6116 | 0.7963          | 52.6051 | 13.5652 |
| 0.9206        | 23.0  | 6394 | 0.7885          | 52.8322 | 13.5669 |
| 0.9012        | 24.0  | 6672 | 0.7818          | 52.9402 | 13.5701 |
| 0.9012        | 25.0  | 6950 | 0.7762          | 53.1182 | 13.5695 |
| 0.8965        | 26.0  | 7228 | 0.7717          | 53.1596 | 13.5612 |
| 0.8836        | 27.0  | 7506 | 0.7681          | 53.3116 | 13.5719 |
| 0.8836        | 28.0  | 7784 | 0.7656          | 53.4399 | 13.5758 |
| 0.8777        | 29.0  | 8062 | 0.7642          | 53.4805 | 13.5737 |
| 0.8777        | 30.0  | 8340 | 0.7636          | 53.5086 | 13.5728 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["opus_infopankki"], "metrics": ["bleu"], "model-index": [{"name": "opus-mt-ar-en-finetuned-ar-to-en", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "opus_infopankki", "type": "opus_infopankki", "args": "ar-en"}, "metrics": [{"type": "bleu", "value": 53.5086, "name": "Bleu"}]}]}]}
transformers pytorch tensorboard marian text2text-generation generated_from_trainer dataset:opus_infopankki license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #generated_from_trainer #dataset-opus_infopankki #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

opus-mt-ar-en-finetuned-ar-to-en
================================


This model is a fine-tuned version of Helsinki-NLP/opus-mt-ar-en on the opus\_infopankki dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7636
* Bleu: 53.5086
* Gen Len: 13.5728


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-06
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #generated_from_trainer #dataset-opus_infopankki #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #generated_from_trainer #dataset-opus_infopankki #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-06
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 30
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.3.2
* Tokenizers 0.12.1