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# m2m100_418M-ja

This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the kde4 dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Bleu: 0.0

## 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: 0.002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step    | Validation Loss | Bleu |
|:-------------:|:-----:|:-------:|:---------------:|:----:|
| 0.0           | 1.0   | 59084   | nan             | 0.0  |
| 0.0           | 2.0   | 118168  | nan             | 0.0  |
| 0.0           | 3.0   | 177252  | nan             | 0.0  |
| 0.0           | 4.0   | 236336  | nan             | 0.0  |
| 0.0           | 5.0   | 295420  | nan             | 0.0  |
| 0.0           | 6.0   | 354504  | nan             | 0.0  |
| 0.0           | 7.0   | 413588  | nan             | 0.0  |
| 0.0           | 8.0   | 472672  | nan             | 0.0  |
| 0.0           | 9.0   | 531756  | nan             | 0.0  |
| 0.0           | 10.0  | 590840  | nan             | 0.0  |
| 0.0           | 11.0  | 649924  | nan             | 0.0  |
| 0.0           | 12.0  | 709008  | nan             | 0.0  |
| 0.0           | 13.0  | 768092  | nan             | 0.0  |
| 0.0           | 14.0  | 827176  | nan             | 0.0  |
| 0.0           | 15.0  | 886260  | nan             | 0.0  |
| 0.0           | 16.0  | 945344  | nan             | 0.0  |
| 0.0           | 17.0  | 1004428 | nan             | 0.0  |
| 0.0           | 18.0  | 1063512 | nan             | 0.0  |
| 0.0           | 19.0  | 1122596 | nan             | 0.0  |
| 0.0           | 20.0  | 1181680 | nan             | 0.0  |
| 0.0           | 21.0  | 1240764 | nan             | 0.0  |
| 0.0           | 22.0  | 1299848 | nan             | 0.0  |
| 0.0           | 23.0  | 1358932 | nan             | 0.0  |
| 0.0           | 24.0  | 1418016 | nan             | 0.0  |
| 0.0           | 25.0  | 1477100 | nan             | 0.0  |
| 0.0           | 26.0  | 1536184 | nan             | 0.0  |
| 0.0           | 27.0  | 1595268 | nan             | 0.0  |
| 0.0           | 28.0  | 1654352 | nan             | 0.0  |
| 0.0           | 29.0  | 1713436 | nan             | 0.0  |
| 0.0           | 30.0  | 1772520 | nan             | 0.0  |
| 0.0           | 31.0  | 1831604 | nan             | 0.0  |
| 0.0           | 32.0  | 1890688 | nan             | 0.0  |
| 0.0           | 33.0  | 1949772 | nan             | 0.0  |
| 0.0           | 34.0  | 2008856 | nan             | 0.0  |
| 0.0           | 35.0  | 2067940 | nan             | 0.0  |
| 0.0           | 36.0  | 2127024 | nan             | 0.0  |
| 0.0           | 37.0  | 2186108 | nan             | 0.0  |
| 0.0           | 38.0  | 2245192 | nan             | 0.0  |
| 0.0           | 39.0  | 2304276 | nan             | 0.0  |
| 0.0           | 40.0  | 2363360 | nan             | 0.0  |
| 0.0           | 41.0  | 2422444 | nan             | 0.0  |
| 0.0           | 42.0  | 2481528 | nan             | 0.0  |
| 0.0           | 43.0  | 2540612 | nan             | 0.0  |
| 0.0           | 44.0  | 2599696 | nan             | 0.0  |
| 0.0           | 45.0  | 2658780 | nan             | 0.0  |
| 0.0           | 46.0  | 2717864 | nan             | 0.0  |
| 0.0           | 47.0  | 2776948 | nan             | 0.0  |
| 0.0           | 48.0  | 2836032 | nan             | 0.0  |
| 0.0           | 49.0  | 2895116 | nan             | 0.0  |
| 0.0           | 50.0  | 2954200 | nan             | 0.0  |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["translation", "generated_from_trainer"], "datasets": ["kde4"], "metrics": ["bleu"], "model-index": [{"name": "m2m100_418M-ja", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "kde4", "type": "kde4", "config": "en-ja", "split": "train", "args": "en-ja"}, "metrics": [{"type": "bleu", "value": 0.0, "name": "Bleu"}]}]}]}
transformers pytorch tensorboard m2m_100 text2text-generation translation generated_from_trainer dataset:kde4 license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #m2m_100 #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

m2m100\_418M-ja
===============


This model is a fine-tuned version of facebook/m2m100\_418M on the kde4 dataset.
It achieves the following results on the evaluation set:


* Loss: nan
* Bleu: 0.0


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: 0.002
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.002
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #m2m_100 #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.002
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #m2m_100 #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.002
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.2