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# iva_mt_wslot-m2m100_418M-en-tr

This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the iva_mt_wslot dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0136
- Bleu: 63.3126
- Gen Len: 19.5834

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.0175        | 1.0   | 2068  | 0.0151          | 59.2285 | 19.5597 |
| 0.0121        | 2.0   | 4136  | 0.0138          | 60.2539 | 19.3643 |
| 0.0087        | 3.0   | 6204  | 0.0134          | 61.6109 | 19.3507 |
| 0.0065        | 4.0   | 8272  | 0.0134          | 61.9941 | 19.6187 |
| 0.0049        | 5.0   | 10340 | 0.0134          | 63.4822 | 19.6174 |
| 0.0039        | 6.0   | 12408 | 0.0136          | 62.9517 | 19.6493 |
| 0.0031        | 7.0   | 14476 | 0.0136          | 63.3126 | 19.5834 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

## Citation

If you use this model, please cite the following:
```
@article{Sowanski2023SlotLI,
  title={Slot Lost in Translation? Not Anymore: A Machine Translation Model for Virtual Assistants with Type-Independent Slot Transfer},
  author={Marcin Sowanski and Artur Janicki},
  journal={2023 30th International Conference on Systems, Signals and Image Processing (IWSSIP)},
  year={2023},
  pages={1-5}
}
```
{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["iva_mt_wslot"], "metrics": ["bleu"], "model-index": [{"name": "iva_mt_wslot-m2m100_418M-en-tr", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "iva_mt_wslot", "type": "iva_mt_wslot", "config": "en-tr", "split": "validation", "args": "en-tr"}, "metrics": [{"type": "bleu", "value": 63.3126, "name": "Bleu"}]}]}]}
transformers pytorch tensorboard m2m_100 text2text-generation generated_from_trainer dataset:iva_mt_wslot doi:10.57967/hf/1527 license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #m2m_100 #text2text-generation #generated_from_trainer #dataset-iva_mt_wslot #doi-10.57967/hf/1527 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

iva\_mt\_wslot-m2m100\_418M-en-tr
=================================


This model is a fine-tuned version of facebook/m2m100\_418M on the iva\_mt\_wslot dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0136
* Bleu: 63.3126
* Gen Len: 19.5834


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: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3


If you use this model, please cite the following:



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3


If you use this model, please cite the following:
TAGS
#transformers #pytorch #tensorboard #m2m_100 #text2text-generation #generated_from_trainer #dataset-iva_mt_wslot #doi-10.57967/hf/1527 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3


If you use this model, please cite the following: