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--- |
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license: apache-2.0 |
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base_model: Helsinki-NLP/opus-mt-en-ro |
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tags: |
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- generated_from_trainer |
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datasets: |
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- arrow |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-en-bkm-Final-37 |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: arrow |
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type: arrow |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 0.8035 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# opus-mt-en-bkm-Final-37 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1287 |
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- Bleu: 0.8035 |
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- Gen Len: 8.152 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| |
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| No log | 1.0 | 364 | 2.7636 | 1.8891 | 7.3867 | |
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| 3.6413 | 2.0 | 728 | 2.4732 | 1.2427 | 7.7232 | |
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| 2.5061 | 3.0 | 1092 | 2.3356 | 0.2297 | 8.558 | |
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| 2.5061 | 4.0 | 1456 | 2.2540 | 0.4676 | 8.8199 | |
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| 2.212 | 5.0 | 1820 | 2.2023 | 0.4941 | 9.0923 | |
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| 2.0058 | 6.0 | 2184 | 2.1658 | 0.665 | 8.627 | |
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| 1.8426 | 7.0 | 2548 | 2.1516 | 0.7263 | 8.4051 | |
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| 1.8426 | 8.0 | 2912 | 2.1404 | 0.7423 | 8.3173 | |
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| 1.7227 | 9.0 | 3276 | 2.1323 | 0.7364 | 8.3373 | |
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| 1.6471 | 10.0 | 3640 | 2.1287 | 0.8035 | 8.152 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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