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Mirelle
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t5-small-finetuned-ro-to-en

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - wmt16
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+ metrics:
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+ - bleu
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+ model-index:
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+ - name: t5-small-finetuned-ro-to-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: wmt16
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+ type: wmt16
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+ args: ro-en
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+ metrics:
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+ - name: Bleu
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+ type: bleu
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+ value: 13.4499
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+ ---
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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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+
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+ # t5-small-finetuned-ro-to-en
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+
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wmt16 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5877
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+ - Bleu: 13.4499
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+ - Gen Len: 17.5073
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: 1
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
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+ | 1.6167 | 0.05 | 2000 | 1.8649 | 9.7029 | 17.5753 |
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+ | 1.4551 | 0.1 | 4000 | 1.7810 | 10.6382 | 17.5358 |
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+ | 1.3723 | 0.16 | 6000 | 1.7369 | 11.1285 | 17.5158 |
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+ | 1.3373 | 0.21 | 8000 | 1.7086 | 11.6173 | 17.5013 |
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+ | 1.2935 | 0.26 | 10000 | 1.6890 | 12.0641 | 17.5038 |
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+ | 1.2632 | 0.31 | 12000 | 1.6670 | 12.3012 | 17.5253 |
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+ | 1.2463 | 0.37 | 14000 | 1.6556 | 12.3991 | 17.5153 |
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+ | 1.2272 | 0.42 | 16000 | 1.6442 | 12.7392 | 17.4732 |
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+ | 1.2052 | 0.47 | 18000 | 1.6328 | 12.8446 | 17.5143 |
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+ | 1.1985 | 0.52 | 20000 | 1.6233 | 13.0892 | 17.4807 |
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+ | 1.1821 | 0.58 | 22000 | 1.6153 | 13.1529 | 17.4952 |
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+ | 1.1791 | 0.63 | 24000 | 1.6079 | 13.2964 | 17.5088 |
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+ | 1.1698 | 0.68 | 26000 | 1.6038 | 13.3548 | 17.4842 |
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+ | 1.154 | 0.73 | 28000 | 1.5957 | 13.3012 | 17.5053 |
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+ | 1.1634 | 0.79 | 30000 | 1.5931 | 13.4203 | 17.5083 |
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+ | 1.1487 | 0.84 | 32000 | 1.5893 | 13.3959 | 17.5123 |
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+ | 1.1495 | 0.89 | 34000 | 1.5875 | 13.3745 | 17.4902 |
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+ | 1.1458 | 0.94 | 36000 | 1.5877 | 13.4129 | 17.5043 |
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+ | 1.1465 | 1.0 | 38000 | 1.5877 | 13.4499 | 17.5073 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.12.5
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.16.1
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+ - Tokenizers 0.10.3