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t5-small-finetuned-it-to-en

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
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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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+ - ccmatrix
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+ metrics:
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+ - bleu
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+ model-index:
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+ - name: t5-small-finetuned-it-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: ccmatrix
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+ type: ccmatrix
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+ config: en-it
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+ split: train[3000:12000]
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+ args: en-it
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+ metrics:
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+ - name: Bleu
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+ type: bleu
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+ value: 13.5927
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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-it-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 ccmatrix dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.4066
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+ - Bleu: 13.5927
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+ - Gen Len: 28.6473
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: 40
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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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+ | No log | 1.0 | 282 | 2.9032 | 7.2452 | 35.1327 |
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+ | 3.2663 | 2.0 | 564 | 2.8156 | 8.3336 | 31.2673 |
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+ | 3.2663 | 3.0 | 846 | 2.7615 | 9.1403 | 30.248 |
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+ | 3.0467 | 4.0 | 1128 | 2.7211 | 9.2676 | 30.2893 |
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+ | 3.0467 | 5.0 | 1410 | 2.6872 | 9.5597 | 30.4067 |
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+ | 2.9575 | 6.0 | 1692 | 2.6600 | 9.907 | 30.3153 |
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+ | 2.9575 | 7.0 | 1974 | 2.6361 | 10.2292 | 29.902 |
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+ | 2.8814 | 8.0 | 2256 | 2.6132 | 10.4384 | 30.1187 |
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+ | 2.8284 | 9.0 | 2538 | 2.5930 | 10.572 | 30.0447 |
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+ | 2.8284 | 10.0 | 2820 | 2.5774 | 10.9557 | 29.5547 |
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+ | 2.7827 | 11.0 | 3102 | 2.5604 | 11.1435 | 29.5847 |
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+ | 2.7827 | 12.0 | 3384 | 2.5484 | 11.4067 | 29.4807 |
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+ | 2.7496 | 13.0 | 3666 | 2.5342 | 11.569 | 29.5827 |
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+ | 2.7496 | 14.0 | 3948 | 2.5208 | 11.7581 | 30.07 |
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+ | 2.7094 | 15.0 | 4230 | 2.5105 | 11.9629 | 29.6993 |
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+ | 2.6764 | 16.0 | 4512 | 2.5007 | 12.2675 | 29.1 |
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+ | 2.6764 | 17.0 | 4794 | 2.4916 | 12.2227 | 29.4 |
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+ | 2.6516 | 18.0 | 5076 | 2.4817 | 12.3529 | 29.222 |
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+ | 2.6516 | 19.0 | 5358 | 2.4747 | 12.6053 | 29.036 |
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+ | 2.6271 | 20.0 | 5640 | 2.4672 | 12.6659 | 29.0993 |
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+ | 2.6271 | 21.0 | 5922 | 2.4602 | 12.8286 | 29.2087 |
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+ | 2.602 | 22.0 | 6204 | 2.4546 | 12.8915 | 29.0233 |
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+ | 2.602 | 23.0 | 6486 | 2.4486 | 12.7892 | 29.2173 |
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+ | 2.5922 | 24.0 | 6768 | 2.4438 | 12.8928 | 29.042 |
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+ | 2.5781 | 25.0 | 7050 | 2.4386 | 13.1954 | 28.8607 |
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+ | 2.5781 | 26.0 | 7332 | 2.4341 | 13.0077 | 28.8367 |
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+ | 2.5578 | 27.0 | 7614 | 2.4306 | 13.1084 | 28.7487 |
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+ | 2.5578 | 28.0 | 7896 | 2.4258 | 13.0929 | 28.9067 |
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+ | 2.5477 | 29.0 | 8178 | 2.4236 | 13.2008 | 28.966 |
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+ | 2.5477 | 30.0 | 8460 | 2.4203 | 13.3476 | 28.7133 |
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+ | 2.5331 | 31.0 | 8742 | 2.4170 | 13.3539 | 28.8787 |
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+ | 2.5312 | 32.0 | 9024 | 2.4148 | 13.3781 | 28.742 |
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+ | 2.5312 | 33.0 | 9306 | 2.4130 | 13.3425 | 28.8393 |
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+ | 2.5234 | 34.0 | 9588 | 2.4113 | 13.4549 | 28.732 |
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+ | 2.5234 | 35.0 | 9870 | 2.4099 | 13.5228 | 28.8313 |
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+ | 2.5131 | 36.0 | 10152 | 2.4084 | 13.547 | 28.6733 |
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+ | 2.5131 | 37.0 | 10434 | 2.4076 | 13.6099 | 28.5193 |
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+ | 2.5101 | 38.0 | 10716 | 2.4071 | 13.5853 | 28.64 |
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+ | 2.5101 | 39.0 | 10998 | 2.4067 | 13.572 | 28.6687 |
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+ | 2.5136 | 40.0 | 11280 | 2.4066 | 13.5927 | 28.6473 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.22.1
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+ - Pytorch 1.12.1
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+ - Datasets 2.5.1
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+ - Tokenizers 0.11.0