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# easyword_model

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7704
- Bleu: 9.5346
- Gen Len: 6.2609

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 31   | 3.4204          | 4.1421 | 6.7329  |
| No log        | 2.0   | 62   | 3.2154          | 4.8111 | 5.9255  |
| No log        | 3.0   | 93   | 3.1073          | 5.8324 | 5.9317  |
| No log        | 4.0   | 124  | 3.0242          | 8.0401 | 5.8944  |
| No log        | 5.0   | 155  | 2.9829          | 5.0246 | 6.0435  |
| No log        | 6.0   | 186  | 2.9363          | 8.2048 | 5.9752  |
| No log        | 7.0   | 217  | 2.9103          | 5.9443 | 6.0186  |
| No log        | 8.0   | 248  | 2.8834          | 6.0896 | 6.0373  |
| No log        | 9.0   | 279  | 2.8792          | 6.0346 | 6.0621  |
| No log        | 10.0  | 310  | 2.8772          | 6.0639 | 6.0497  |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "easyword_model", "results": []}]}
transformers pytorch m2m_100 text2text-generation generated_from_trainer license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 

easyword\_model
===============


This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.7704
* Bleu: 9.5346
* Gen Len: 6.2609


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: 10
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3