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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-en-pl-plaintext_10e
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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-pl
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split: validation
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args: en-pl
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metrics:
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- name: Bleu
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type: bleu
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value: 41.3124
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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-en-pl-plaintext_10e
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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: 0.0169
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- Bleu: 41.3124
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- Gen Len: 15.5197
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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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| 0.0169 | 1.0 | 5091 | 0.0162 | 36.663 | 15.6444 |
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| 0.0124 | 2.0 | 10182 | 0.0151 | 38.36 | 15.6314 |
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| 0.0086 | 3.0 | 15273 | 0.0150 | 39.3808 | 15.5507 |
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| 0.0069 | 4.0 | 20364 | 0.0152 | 39.6307 | 15.5235 |
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| 0.0049 | 5.0 | 25455 | 0.0156 | 40.4441 | 15.5911 |
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| 0.0038 | 6.0 | 30546 | 0.0159 | 40.3781 | 15.47 |
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| 0.0027 | 7.0 | 35637 | 0.0163 | 40.1339 | 15.4722 |
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| 0.0021 | 8.0 | 40728 | 0.0166 | 41.4429 | 15.4906 |
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| 0.0016 | 9.0 | 45819 | 0.0168 | 41.1024 | 15.5249 |
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| 0.0012 | 10.0 | 50910 | 0.0169 | 41.3124 | 15.5197 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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