---
license: cc-by-4.0
base_model: Helsinki-NLP/opus-mt-tc-big-hu-en
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-tc-big-hu-en-finetuned-news
  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. -->

# opus-mt-tc-big-hu-en-finetuned-news

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tc-big-hu-en](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-hu-en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1412
- Bleu: 40.3642
- Gen Len: 44.0303

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 0.11  | 100  | 1.1822          | 38.1953 | 43.5551 |
| No log        | 0.22  | 200  | 1.1738          | 38.6712 | 43.549  |
| No log        | 0.32  | 300  | 1.1602          | 39.2014 | 44.2009 |
| No log        | 0.43  | 400  | 1.1503          | 39.2141 | 43.9468 |
| 1.2199        | 0.54  | 500  | 1.1451          | 39.2687 | 43.6871 |
| 1.2199        | 0.65  | 600  | 1.1349          | 39.445  | 43.9483 |
| 1.2199        | 0.75  | 700  | 1.1356          | 39.3787 | 43.47   |
| 1.2199        | 0.86  | 800  | 1.1233          | 39.7025 | 43.9054 |
| 1.2199        | 0.97  | 900  | 1.1224          | 39.9764 | 43.9656 |
| 1.1308        | 1.08  | 1000 | 1.1343          | 39.8533 | 43.9929 |
| 1.1308        | 1.19  | 1100 | 1.1446          | 39.7232 | 43.675  |
| 1.1308        | 1.29  | 1200 | 1.1378          | 40.0687 | 44.0606 |
| 1.1308        | 1.4   | 1300 | 1.1324          | 39.9239 | 43.7738 |
| 1.1308        | 1.51  | 1400 | 1.1330          | 40.0318 | 43.7756 |
| 0.8661        | 1.62  | 1500 | 1.1315          | 39.8677 | 43.7542 |
| 0.8661        | 1.72  | 1600 | 1.1185          | 40.1978 | 44.168  |
| 0.8661        | 1.83  | 1700 | 1.1298          | 40.254  | 44.0497 |
| 0.8661        | 1.94  | 1800 | 1.1191          | 40.2197 | 44.0295 |
| 0.8661        | 2.05  | 1900 | 1.1416          | 40.1255 | 44.0534 |
| 0.8198        | 2.16  | 2000 | 1.1479          | 40.3099 | 43.9854 |
| 0.8198        | 2.26  | 2100 | 1.1495          | 40.3473 | 44.0204 |
| 0.8198        | 2.37  | 2200 | 1.1453          | 40.329  | 44.0764 |
| 0.8198        | 2.48  | 2300 | 1.1450          | 40.2623 | 44.0944 |
| 0.8198        | 2.59  | 2400 | 1.1471          | 40.416  | 44.1797 |
| 0.6783        | 2.69  | 2500 | 1.1433          | 40.4645 | 44.0817 |
| 0.6783        | 2.8   | 2600 | 1.1405          | 40.4229 | 44.0554 |
| 0.6783        | 2.91  | 2700 | 1.1418          | 40.4142 | 44.0493 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1