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Broomva
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t5-base-translation-spa-guc

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
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Broomva commited on
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End of training

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  1. README.md +24 -13
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3694
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- - Bleu: 0.6133
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- - Gen Len: 18.05
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  ## Model description
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@@ -39,27 +39,38 @@ More information needed
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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: 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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  - lr_scheduler_warmup_steps: 10
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- - num_epochs: 3
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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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- | 1.7203 | 1.0 | 6445 | 1.5225 | 0.5652 | 18.0594 |
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- | 1.5582 | 2.0 | 12890 | 1.4019 | 0.5994 | 18.036 |
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- | 1.5224 | 3.0 | 19335 | 1.3694 | 0.6133 | 18.05 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.35.2
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- - Pytorch 2.1.1+cu121
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0136
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+ - Bleu: 1.4957
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+ - Gen Len: 17.8854
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  ## Model description
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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: 8
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+ - eval_batch_size: 8
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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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  - lr_scheduler_warmup_steps: 10
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+ - num_epochs: 15
 
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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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+ | 1.3933 | 1.0 | 7668 | 1.5107 | 0.8563 | 18.0712 |
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+ | 1.598 | 2.0 | 15336 | 1.3444 | 0.9626 | 18.0648 |
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+ | 1.4277 | 3.0 | 23004 | 1.2551 | 1.1025 | 17.9695 |
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+ | 1.4152 | 4.0 | 30672 | 1.2000 | 1.1361 | 17.9426 |
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+ | 1.1671 | 5.0 | 38340 | 1.1565 | 1.2243 | 17.8416 |
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+ | 1.1777 | 6.0 | 46008 | 1.1217 | 1.2874 | 17.8809 |
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+ | 1.4485 | 7.0 | 53676 | 1.0955 | 1.3318 | 17.9663 |
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+ | 1.3209 | 8.0 | 61344 | 1.0729 | 1.3889 | 17.967 |
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+ | 1.394 | 9.0 | 69012 | 1.0557 | 1.4082 | 17.8646 |
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+ | 1.0608 | 10.0 | 76680 | 1.0435 | 1.4463 | 17.9294 |
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+ | 1.0713 | 11.0 | 84348 | 1.0323 | 1.4558 | 17.9015 |
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+ | 0.976 | 12.0 | 92016 | 1.0248 | 1.4666 | 17.9103 |
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+ | 1.0782 | 13.0 | 99684 | 1.0191 | 1.484 | 17.8929 |
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+ | 1.045 | 14.0 | 107352 | 1.0150 | 1.4869 | 17.8875 |
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+ | 0.9936 | 15.0 | 115020 | 1.0136 | 1.4957 | 17.8854 |
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  ### Framework versions
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  - Transformers 4.35.2
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+ - Pytorch 1.13.1+cu117
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0