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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: MarianMix_en-10
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# MarianMix_en-10

This model is a fine-tuned version of [Helsinki-NLP/opus-tatoeba-en-ja](https://huggingface.co/Helsinki-NLP/opus-tatoeba-en-ja) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6475
- Bleu: 3.3068
- Gen Len: 46.466

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 99
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 1.7048        | 0.44  | 500  | 1.0358          | 0.7054 | 50.216  |
| 0.6727        | 0.89  | 1000 | 0.8751          | 1.1453 | 46.401  |
| 0.5497        | 1.33  | 1500 | 0.7978          | 1.2939 | 46.27   |
| 0.5087        | 1.77  | 2000 | 0.7424          | 1.7606 | 48.227  |
| 0.4488        | 2.22  | 2500 | 0.7176          | 2.1927 | 47.076  |
| 0.4077        | 2.66  | 3000 | 0.6888          | 2.5931 | 46.162  |
| 0.3895        | 3.1   | 3500 | 0.6776          | 2.975  | 45.728  |
| 0.3465        | 3.55  | 4000 | 0.6645          | 2.9679 | 46.047  |
| 0.3464        | 3.99  | 4500 | 0.6533          | 3.435  | 46.317  |
| 0.3119        | 4.43  | 5000 | 0.6517          | 3.4986 | 46.333  |
| 0.3066        | 4.88  | 5500 | 0.6475          | 3.3068 | 46.466  |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.9.1
- Datasets 1.17.0
- Tokenizers 0.10.3