transformers pytorch m2m_100 text2text-generation translation generated_from_trainer dataset:wmt16 base_model:kazandaev/m2m100_418M base_model:finetune:kazandaev/m2m100_418M license:mit model-index autotrain_compatible endpoints_compatible region:us
---
base_model: kazandaev/m2m100_418M
datasets:
- wmt16
license: mit
metrics:
- bleu
tags:
- translation
- generated_from_trainer
model-index:
- name: m2m100_418M
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: wmt16
      type: wmt16
      config: ru-en
      split: validation
      args: ru-en
    metrics:
    - type: bleu
      value: 32.0585
      name: Bleu
---

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# m2m100_418M

This model is a fine-tuned version of [kazandaev/m2m100_418M](https://huggingface.co/kazandaev/m2m100_418M) on the custom en-ru dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8954
- Bleu: 32.0585
- Gen Len: 36.1643

## 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: 2
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.8087        | 1.0   | 47790 | 0.9542          | 30.786  | 36.1469 |
| 0.7266        | 2.0   | 95580 | 0.8954          | 32.0585 | 36.1643 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.2.0.dev20230920+cu121
- Datasets 2.14.4
- Tokenizers 0.13.3
