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update model card README.md
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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- iva_mt_wslot
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metrics:
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- bleu
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model-index:
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- name: iva_mt_wslot-m2m100_418M-zh-en
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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: iva_mt_wslot
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type: iva_mt_wslot
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config: en-zh
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split: validation
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args: en-zh
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metrics:
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- name: Bleu
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type: bleu
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value: 67.9385
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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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# iva_mt_wslot-m2m100_418M-zh-en
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This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the iva_mt_wslot dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0139
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- Bleu: 67.9385
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- Gen Len: 18.9988
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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: 4
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- eval_batch_size: 4
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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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- mixed_precision_training: Native AMP
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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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| 0.016 | 1.0 | 2437 | 0.0138 | 62.077 | 18.6077 |
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| 0.0114 | 2.0 | 4874 | 0.0126 | 64.3834 | 18.9019 |
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| 0.0084 | 3.0 | 7311 | 0.0123 | 66.0012 | 18.9206 |
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| 0.0067 | 4.0 | 9748 | 0.0123 | 66.7838 | 19.0018 |
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| 0.005 | 5.0 | 12185 | 0.0124 | 66.9053 | 18.9527 |
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| 0.0039 | 6.0 | 14622 | 0.0128 | 67.5252 | 18.9918 |
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| 0.003 | 7.0 | 17059 | 0.0131 | 67.3664 | 18.9609 |
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| 0.0025 | 8.0 | 19496 | 0.0135 | 67.792 | 19.0198 |
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| 0.0019 | 9.0 | 21933 | 0.0137 | 67.7256 | 18.9591 |
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| 0.0015 | 10.0 | 24370 | 0.0139 | 67.9385 | 18.9988 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.1.0+cu121
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- Datasets 2.15.0
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- Tokenizers 0.13.3
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