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# tst-translation

This model is a fine-tuned version of [anzorq/kbd_lat-835k_ru-3M_t5-small](https://huggingface.co/anzorq/kbd_lat-835k_ru-3M_t5-small) on the anzorq/kbd_lat-ru anzorq--kbd-ru dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6000
- Bleu: 12.649
- Gen Len: 11.8018

## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 35.0

### Training results



### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 1.16.0
- Tokenizers 0.12.1

{"language": ["ru", "kbd"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["anzorq/kbd_lat-ru"], "metrics": ["bleu"], "widget": [{"text": "ru->kbd: \u042f \u0438\u0434\u0443 \u0434\u043e\u043c\u043e\u0439.", "example_title": "\u042f \u0438\u0434\u0443 \u0434\u043e\u043c\u043e\u0439."}, {"text": "ru->kbd: \u0414\u0435\u0442\u0438 \u0438\u0433\u0440\u0430\u044e\u0442 \u0432\u043e \u0434\u0432\u043e\u0440\u0435.", "example_title": "\u0414\u0435\u0442\u0438 \u0438\u0433\u0440\u0430\u044e\u0442 \u0432\u043e \u0434\u0432\u043e\u0440\u0435."}, {"text": "ru->kbd: \u0421\u043a\u043e\u043b\u044c\u043a\u043e \u0442\u0435\u0431\u0435 \u043b\u0435\u0442?", "example_title": "\u0421\u043a\u043e\u043b\u044c\u043a\u043e \u0442\u0435\u0431\u0435 \u043b\u0435\u0442?"}], "model-index": [{"name": "tst-translation", "results": [{"task": {"type": "translation", "name": "translation"}, "dataset": {"name": "anzorq/kbd_lat-ru anzorq--kbd-ru", "type": "anzorq/kbd_lat-ru", "args": "anzorq--kbd-ru"}, "metrics": [{"type": "bleu", "value": 12.649, "name": "Bleu"}]}]}]}
transformers pytorch safetensors t5 text2text-generation generated_from_trainer ru kbd dataset:anzorq/kbd_lat-ru license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #ru #kbd #dataset-anzorq/kbd_lat-ru #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# tst-translation

This model is a fine-tuned version of anzorq/kbd_lat-835k_ru-3M_t5-small on the anzorq/kbd_lat-ru anzorq--kbd-ru dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6000
- Bleu: 12.649
- Gen Len: 11.8018

## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 35.0

### Training results



### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 1.16.0
- Tokenizers 0.12.1

# tst-translation

This model is a fine-tuned version of anzorq/kbd_lat-835k_ru-3M_t5-small on the anzorq/kbd_lat-ru anzorq--kbd-ru dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6000
- Bleu: 12.649
- Gen Len: 11.8018 ## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 35.0 ### Training results ### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 1.16.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #ru #kbd #dataset-anzorq/kbd_lat-ru #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # tst-translation

This model is a fine-tuned version of anzorq/kbd_lat-835k_ru-3M_t5-small on the anzorq/kbd_lat-ru anzorq--kbd-ru dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6000
- Bleu: 12.649
- Gen Len: 11.8018 ## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 35.0 ### Training results ### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 1.16.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #ru #kbd #dataset-anzorq/kbd_lat-ru #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# tst-translation

This model is a fine-tuned version of anzorq/kbd_lat-835k_ru-3M_t5-small on the anzorq/kbd_lat-ru anzorq--kbd-ru dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6000
- Bleu: 12.649
- Gen Len: 11.8018## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 35.0### Training results### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 1.16.0
- Tokenizers 0.12.1