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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
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: 14.5684
---
<!-- 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
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: 1.1597
- Bleu: 14.5684
- Gen Len: 58.4294
## 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: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 3.3983 | 1.0 | 974 | 1.9251 | 3.7894 | 60.1579 |
| 1.9429 | 2.0 | 1948 | 1.6720 | 5.7083 | 58.6443 |
| 1.7118 | 3.0 | 2922 | 1.5389 | 7.1977 | 58.8536 |
| 1.5647 | 4.0 | 3896 | 1.4484 | 8.4631 | 57.9068 |
| 1.4611 | 5.0 | 4870 | 1.3836 | 9.5314 | 59.3106 |
| 1.3735 | 6.0 | 5844 | 1.3357 | 10.1879 | 59.5501 |
| 1.3078 | 7.0 | 6818 | 1.3014 | 10.9172 | 59.4968 |
| 1.245 | 8.0 | 7792 | 1.2737 | 11.445 | 59.585 |
| 1.2048 | 9.0 | 8766 | 1.2485 | 11.9346 | 58.3275 |
| 1.1648 | 10.0 | 9740 | 1.2298 | 12.3049 | 58.7768 |
| 1.1272 | 11.0 | 10714 | 1.2176 | 12.7287 | 58.1549 |
| 1.086 | 12.0 | 11688 | 1.2043 | 13.0962 | 59.2217 |
| 1.0595 | 13.0 | 12662 | 1.1973 | 13.3375 | 58.6736 |
| 1.0343 | 14.0 | 13636 | 1.1844 | 13.3963 | 58.2763 |
| 1.0174 | 15.0 | 14610 | 1.1797 | 13.7067 | 58.1738 |
| 0.9923 | 16.0 | 15584 | 1.1757 | 13.9467 | 59.3246 |
| 0.9703 | 17.0 | 16558 | 1.1704 | 14.1023 | 58.9813 |
| 0.9589 | 18.0 | 17532 | 1.1663 | 14.2842 | 58.401 |
| 0.9472 | 19.0 | 18506 | 1.1662 | 14.2109 | 58.4796 |
| 0.9262 | 20.0 | 19480 | 1.1635 | 14.3872 | 58.1601 |
| 0.9147 | 21.0 | 20454 | 1.1606 | 14.4983 | 58.7417 |
| 0.9162 | 22.0 | 21428 | 1.1630 | 14.5229 | 58.4345 |
| 0.9012 | 23.0 | 22402 | 1.1607 | 14.6204 | 58.0767 |
| 0.899 | 24.0 | 23376 | 1.1600 | 14.5681 | 58.4357 |
| 0.8934 | 25.0 | 24350 | 1.1597 | 14.5684 | 58.4294 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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