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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: t5-base-translation-spa-guc
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-translation-spa-guc
This model is a fine-tuned version of [t5-base](https://huggingface.co./t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0136
- Bleu: 1.4957
- Gen Len: 17.8854
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|
| 1.3933 | 1.0 | 7668 | 1.5107 | 0.8563 | 18.0712 |
| 1.598 | 2.0 | 15336 | 1.3444 | 0.9626 | 18.0648 |
| 1.4277 | 3.0 | 23004 | 1.2551 | 1.1025 | 17.9695 |
| 1.4152 | 4.0 | 30672 | 1.2000 | 1.1361 | 17.9426 |
| 1.1671 | 5.0 | 38340 | 1.1565 | 1.2243 | 17.8416 |
| 1.1777 | 6.0 | 46008 | 1.1217 | 1.2874 | 17.8809 |
| 1.4485 | 7.0 | 53676 | 1.0955 | 1.3318 | 17.9663 |
| 1.3209 | 8.0 | 61344 | 1.0729 | 1.3889 | 17.967 |
| 1.394 | 9.0 | 69012 | 1.0557 | 1.4082 | 17.8646 |
| 1.0608 | 10.0 | 76680 | 1.0435 | 1.4463 | 17.9294 |
| 1.0713 | 11.0 | 84348 | 1.0323 | 1.4558 | 17.9015 |
| 0.976 | 12.0 | 92016 | 1.0248 | 1.4666 | 17.9103 |
| 1.0782 | 13.0 | 99684 | 1.0191 | 1.484 | 17.8929 |
| 1.045 | 14.0 | 107352 | 1.0150 | 1.4869 | 17.8875 |
| 0.9936 | 15.0 | 115020 | 1.0136 | 1.4957 | 17.8854 |
### Framework versions
- Transformers 4.35.2
- Pytorch 1.13.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
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