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--- |
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license: mit |
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base_model: facebook/m2m100_418M |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: output |
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results: [] |
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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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# output |
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This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1802 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.7737 | 0.11 | 100 | 0.4133 | |
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| 0.3772 | 0.23 | 200 | 0.2586 | |
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| 0.2884 | 0.34 | 300 | 0.2401 | |
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| 0.2732 | 0.46 | 400 | 0.2320 | |
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| 0.285 | 0.57 | 500 | 0.2212 | |
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| 0.2375 | 0.69 | 600 | 0.2143 | |
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| 0.232 | 0.8 | 700 | 0.2113 | |
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| 0.2468 | 0.91 | 800 | 0.2028 | |
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| 0.2222 | 1.03 | 900 | 0.1996 | |
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| 0.1715 | 1.14 | 1000 | 0.1971 | |
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| 0.1442 | 1.26 | 1100 | 0.1949 | |
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| 0.1726 | 1.37 | 1200 | 0.1936 | |
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| 0.1359 | 1.49 | 1300 | 0.1932 | |
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| 0.1613 | 1.6 | 1400 | 0.1912 | |
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| 0.1599 | 1.71 | 1500 | 0.1886 | |
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| 0.1431 | 1.83 | 1600 | 0.1856 | |
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| 0.1607 | 1.94 | 1700 | 0.1829 | |
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| 0.1269 | 2.06 | 1800 | 0.1867 | |
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| 0.0838 | 2.17 | 1900 | 0.1837 | |
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| 0.0982 | 2.29 | 2000 | 0.1850 | |
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| 0.0936 | 2.4 | 2100 | 0.1831 | |
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| 0.1009 | 2.51 | 2200 | 0.1832 | |
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| 0.0889 | 2.63 | 2300 | 0.1824 | |
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| 0.0956 | 2.74 | 2400 | 0.1813 | |
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| 0.0967 | 2.86 | 2500 | 0.1807 | |
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| 0.1075 | 2.97 | 2600 | 0.1802 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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