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t5-base_ro-finetuned-en-to-it

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
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+ ---
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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-base_ro-finetuned-en-to-it
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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: 19.6396
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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-base_ro-finetuned-en-to-it
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+
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+ This model is a fine-tuned version of [j0hngou/t5-base-finetuned-en-to-ro](https://huggingface.co/j0hngou/t5-base-finetuned-en-to-ro) on the ccmatrix dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4669
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+ - Bleu: 19.6396
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+ - Gen Len: 52.4247
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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 | 2.0942 | 5.6875 | 73.434 |
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+ | 2.5108 | 2.0 | 564 | 1.9725 | 6.6631 | 72.6607 |
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+ | 2.5108 | 3.0 | 846 | 1.9010 | 7.9227 | 67.01 |
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+ | 2.1659 | 4.0 | 1128 | 1.8452 | 8.9935 | 65.1027 |
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+ | 2.1659 | 5.0 | 1410 | 1.7979 | 9.4164 | 64.9827 |
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+ | 2.0288 | 6.0 | 1692 | 1.7590 | 9.6035 | 66.6933 |
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+ | 2.0288 | 7.0 | 1974 | 1.7264 | 10.7658 | 62.068 |
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+ | 1.9238 | 8.0 | 2256 | 1.6955 | 11.5779 | 59.472 |
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+ | 1.8435 | 9.0 | 2538 | 1.6729 | 12.7588 | 56.584 |
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+ | 1.8435 | 10.0 | 2820 | 1.6541 | 13.3086 | 56.1153 |
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+ | 1.775 | 11.0 | 3102 | 1.6337 | 13.8543 | 55.3307 |
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+ | 1.775 | 12.0 | 3384 | 1.6148 | 14.3566 | 55.2853 |
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+ | 1.7204 | 13.0 | 3666 | 1.5994 | 14.693 | 55.6607 |
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+ | 1.7204 | 14.0 | 3948 | 1.5838 | 15.1284 | 55.5327 |
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+ | 1.6705 | 15.0 | 4230 | 1.5742 | 15.6125 | 55.0087 |
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+ | 1.632 | 16.0 | 4512 | 1.5600 | 15.9616 | 54.052 |
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+ | 1.632 | 17.0 | 4794 | 1.5526 | 16.495 | 53.562 |
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+ | 1.5868 | 18.0 | 5076 | 1.5392 | 16.4252 | 54.4613 |
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+ | 1.5868 | 19.0 | 5358 | 1.5311 | 16.753 | 54.1853 |
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+ | 1.5656 | 20.0 | 5640 | 1.5262 | 17.0308 | 54.2473 |
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+ | 1.5656 | 21.0 | 5922 | 1.5186 | 17.3553 | 53.396 |
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+ | 1.529 | 22.0 | 6204 | 1.5121 | 17.6177 | 53.472 |
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+ | 1.529 | 23.0 | 6486 | 1.5058 | 17.6409 | 53.6847 |
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+ | 1.5071 | 24.0 | 6768 | 1.5038 | 18.2009 | 53.2327 |
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+ | 1.4903 | 25.0 | 7050 | 1.4962 | 18.4838 | 52.9587 |
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+ | 1.4903 | 26.0 | 7332 | 1.4935 | 18.5545 | 52.688 |
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+ | 1.4686 | 27.0 | 7614 | 1.4879 | 18.62 | 53.5 |
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+ | 1.4686 | 28.0 | 7896 | 1.4850 | 19.0099 | 52.34 |
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+ | 1.4511 | 29.0 | 8178 | 1.4813 | 19.0538 | 52.474 |
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+ | 1.4511 | 30.0 | 8460 | 1.4787 | 18.89 | 53.0753 |
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+ | 1.4364 | 31.0 | 8742 | 1.4756 | 19.2582 | 52.3587 |
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+ | 1.4279 | 32.0 | 9024 | 1.4739 | 19.2973 | 52.69 |
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+ | 1.4279 | 33.0 | 9306 | 1.4725 | 19.3624 | 52.694 |
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+ | 1.4172 | 34.0 | 9588 | 1.4704 | 19.5421 | 52.1667 |
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+ | 1.4172 | 35.0 | 9870 | 1.4689 | 19.4807 | 52.5487 |
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+ | 1.4141 | 36.0 | 10152 | 1.4685 | 19.5972 | 52.2733 |
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+ | 1.4141 | 37.0 | 10434 | 1.4676 | 19.5835 | 52.374 |
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+ | 1.4058 | 38.0 | 10716 | 1.4674 | 19.6374 | 52.3447 |
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+ | 1.4058 | 39.0 | 10998 | 1.4671 | 19.6105 | 52.5273 |
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+ | 1.4027 | 40.0 | 11280 | 1.4669 | 19.6396 | 52.4247 |
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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