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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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- cartesinus/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 |
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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: 69.2836 |
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language: |
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- en |
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- es |
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pipeline_tag: translation |
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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 |
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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: 0.0115 |
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- Bleu: 69.2836 |
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- Gen Len: 20.2064 |
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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: 7 |
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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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| 0.0135 | 1.0 | 2104 | 0.0122 | 66.8284 | 20.2851 | |
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| 0.009 | 2.0 | 4208 | 0.0112 | 68.1164 | 20.1501 | |
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| 0.0067 | 3.0 | 6312 | 0.0110 | 68.256 | 20.0603 | |
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| 0.0051 | 4.0 | 8416 | 0.0110 | 68.7002 | 20.1219 | |
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| 0.0037 | 5.0 | 10520 | 0.0112 | 68.699 | 20.2733 | |
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| 0.0027 | 6.0 | 12624 | 0.0113 | 68.9916 | 20.209 | |
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| 0.0023 | 7.0 | 14728 | 0.0115 | 69.2836 | 20.2064 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
