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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-es-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-es
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split: validation
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args: en-es
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metrics:
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- name: Bleu
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type: bleu
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value: 51.1501
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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-es-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: 0.0116
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- Bleu: 51.1501
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- Gen Len: 12.6861
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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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| 0.012 | 1.0 | 2104 | 0.0109 | 47.9124 | 12.7523 |
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| 0.0079 | 2.0 | 4208 | 0.0101 | 49.9897 | 12.6763 |
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| 0.0059 | 3.0 | 6312 | 0.0101 | 50.5286 | 12.6435 |
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| 0.0045 | 4.0 | 8416 | 0.0101 | 49.6821 | 12.5472 |
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| 0.0033 | 5.0 | 10520 | 0.0104 | 50.3856 | 12.6638 |
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| 0.0024 | 6.0 | 12624 | 0.0107 | 50.359 | 12.7418 |
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| 0.0019 | 7.0 | 14728 | 0.0111 | 50.8234 | 12.709 |
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| 0.0014 | 8.0 | 16832 | 0.0111 | 50.872 | 12.6671 |
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| 0.0011 | 9.0 | 18936 | 0.0114 | 51.3014 | 12.6291 |
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| 0.001 | 10.0 | 21040 | 0.0116 | 51.1501 | 12.6861 |
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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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