---
base_model: Tobius/opus-mt-en-lg-finetuned-en-to-lg
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-en-lg-finetuned-en-to-lg-finetuned-en-to-lm
  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-en-lg-finetuned-en-to-lg-finetuned-en-to-lm

This model is a fine-tuned version of [Tobius/opus-mt-en-lg-finetuned-en-to-lg](https://huggingface.co/Tobius/opus-mt-en-lg-finetuned-en-to-lg) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7639
- Bleu: 30.9462
- Gen Len: 21.6305

## 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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 146  | 3.6537          | 0.5489  | 30.8399 |
| No log        | 2.0   | 292  | 3.0866          | 0.5298  | 22.7759 |
| No log        | 3.0   | 438  | 2.7528          | 0.8364  | 26.5419 |
| 3.8771        | 4.0   | 584  | 2.4983          | 1.6885  | 25.3966 |
| 3.8771        | 5.0   | 730  | 2.2893          | 2.265   | 23.0296 |
| 3.8771        | 6.0   | 876  | 2.1164          | 3.5594  | 21.9409 |
| 2.5379        | 7.0   | 1022 | 1.9606          | 3.8191  | 22.8325 |
| 2.5379        | 8.0   | 1168 | 1.8145          | 4.7176  | 22.5025 |
| 2.5379        | 9.0   | 1314 | 1.6974          | 5.5036  | 21.7931 |
| 2.5379        | 10.0  | 1460 | 1.5895          | 7.0622  | 21.9483 |
| 2.0088        | 11.0  | 1606 | 1.4934          | 7.9064  | 22.2143 |
| 2.0088        | 12.0  | 1752 | 1.4120          | 8.7831  | 20.9754 |
| 2.0088        | 13.0  | 1898 | 1.3244          | 10.7815 | 21.899  |
| 1.6503        | 14.0  | 2044 | 1.2544          | 11.9959 | 21.835  |
| 1.6503        | 15.0  | 2190 | 1.1843          | 12.9721 | 21.766  |
| 1.6503        | 16.0  | 2336 | 1.1271          | 15.3546 | 21.5542 |
| 1.6503        | 17.0  | 2482 | 1.0670          | 15.9538 | 21.7906 |
| 1.3905        | 18.0  | 2628 | 1.0184          | 19.1229 | 21.9212 |
| 1.3905        | 19.0  | 2774 | 0.9797          | 20.3025 | 21.0148 |
| 1.3905        | 20.0  | 2920 | 0.9358          | 22.3064 | 21.6946 |
| 1.1903        | 21.0  | 3066 | 0.9012          | 24.9192 | 21.3128 |
| 1.1903        | 22.0  | 3212 | 0.8704          | 25.8138 | 21.3202 |
| 1.1903        | 23.0  | 3358 | 0.8481          | 26.8542 | 21.5591 |
| 1.0573        | 24.0  | 3504 | 0.8228          | 28.4838 | 21.3251 |
| 1.0573        | 25.0  | 3650 | 0.8069          | 29.1448 | 21.399  |
| 1.0573        | 26.0  | 3796 | 0.7892          | 29.8567 | 21.5985 |
| 1.0573        | 27.0  | 3942 | 0.7777          | 29.8862 | 21.6404 |
| 0.9649        | 28.0  | 4088 | 0.7703          | 30.9483 | 21.7315 |
| 0.9649        | 29.0  | 4234 | 0.7660          | 30.9831 | 21.6108 |
| 0.9649        | 30.0  | 4380 | 0.7639          | 30.9462 | 21.6305 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2