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---
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-ro
tags:
- generated_from_trainer
datasets:
- arrow
metrics:
- bleu
model-index:
- name: opus-mt-en-bkm-Final-37
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: arrow
      type: arrow
      config: default
      split: train
      args: default
    metrics:
    - name: Bleu
      type: bleu
      value: 0.8035
---

<!-- 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-bkm-Final-37

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ro](https://huggingface.co/Helsinki-NLP/opus-mt-en-ro) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1287
- Bleu: 0.8035
- Gen Len: 8.152

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 364  | 2.7636          | 1.8891 | 7.3867  |
| 3.6413        | 2.0   | 728  | 2.4732          | 1.2427 | 7.7232  |
| 2.5061        | 3.0   | 1092 | 2.3356          | 0.2297 | 8.558   |
| 2.5061        | 4.0   | 1456 | 2.2540          | 0.4676 | 8.8199  |
| 2.212         | 5.0   | 1820 | 2.2023          | 0.4941 | 9.0923  |
| 2.0058        | 6.0   | 2184 | 2.1658          | 0.665  | 8.627   |
| 1.8426        | 7.0   | 2548 | 2.1516          | 0.7263 | 8.4051  |
| 1.8426        | 8.0   | 2912 | 2.1404          | 0.7423 | 8.3173  |
| 1.7227        | 9.0   | 3276 | 2.1323          | 0.7364 | 8.3373  |
| 1.6471        | 10.0  | 3640 | 2.1287          | 0.8035 | 8.152   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2