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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-10e
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: 6.3359
---
<!-- 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-10e
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: 1.6318
- Bleu: 6.3359
- Gen Len: 58.0829
## 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: 128
- eval_batch_size: 128
- 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 | 140 | 3.1399 | 0.0997 | 69.5849 |
| No log | 2.0 | 280 | 2.2017 | 1.6584 | 62.2953 |
| No log | 3.0 | 420 | 1.9380 | 3.61 | 59.1948 |
| 3.0959 | 4.0 | 560 | 1.8188 | 4.5827 | 57.0106 |
| 3.0959 | 5.0 | 700 | 1.7496 | 5.1558 | 56.731 |
| 3.0959 | 6.0 | 840 | 1.7012 | 5.6941 | 58.2515 |
| 3.0959 | 7.0 | 980 | 1.6683 | 5.964 | 57.0337 |
| 1.851 | 8.0 | 1120 | 1.6473 | 6.1539 | 57.0685 |
| 1.851 | 9.0 | 1260 | 1.6357 | 6.3233 | 57.5607 |
| 1.851 | 10.0 | 1400 | 1.6318 | 6.3359 | 58.0829 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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