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---
language:
- de
- en
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
datasets:
- lilferrit/wmt14-short
metrics:
- bleu
model-index:
- name: ft-wmt14-5
results:
- task:
name: Translation
type: translation
dataset:
name: lilferrit/wmt14-short
type: lilferrit/wmt14-short
metrics:
- name: Bleu
type: bleu
value: 20.7584
---
<!-- 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. -->
# ft-wmt14-5
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the lilferrit/wmt14-short dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0604
- Bleu: 20.7584
- Gen Len: 30.499
## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adafactor
- lr_scheduler_type: constant
- training_steps: 100000
### Training results
| Training Loss | Epoch | Step | Bleu | Gen Len | Validation Loss |
|:-------------:|:------:|:------:|:-------:|:-------:|:---------------:|
| 1.9166 | 0.2778 | 10000 | 15.8119 | 32.097 | 2.3105 |
| 1.7184 | 0.5556 | 20000 | 17.5903 | 31.1153 | 2.1993 |
| 1.6061 | 0.8333 | 30000 | 18.9604 | 30.327 | 2.1380 |
| 1.516 | 1.1111 | 40000 | 19.1444 | 30.2727 | 2.1366 |
| 1.4675 | 1.3889 | 50000 | 19.7588 | 30.1127 | 2.1208 |
| 1.4416 | 1.6667 | 60000 | 19.9263 | 30.4463 | 2.0889 |
| 1.4111 | 1.9444 | 70000 | 2.0795 | 20.3323 | 30.1207 |
| 1.3603 | 2.2222 | 80000 | 2.0850 | 20.5373 | 30.5943 |
| 1.3378 | 2.5 | 90000 | 2.0604 | 20.7584 | 30.499 |
| 1.3381 | 2.7778 | 100000 | 2.0597 | 20.6113 | 30.701 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|