Translation
Transformers
PyTorch
English
Romanian
mt5
text2text-generation
wmt16
Lvxue
Eval Results (legacy)
# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM
tokenizer = AutoTokenizer.from_pretrained("Lvxue/finetuned-mt5-small-10epoch")
model = AutoModelForMultimodalLM.from_pretrained("Lvxue/finetuned-mt5-small-10epoch")Quick Links
finetuned-mt5-small-10epoch
This model is a fine-tuned version of google/mt5-small on the wmt16 ro-en dataset. It achieves the following results on the evaluation set:
- Loss: 1.7274
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: 5e-05
- train_batch_size: 48
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
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Dataset used to train Lvxue/finetuned-mt5-small-10epoch
Evaluation results
- BLEU on wmt16test set self-reported6.001
- loss on wmt16test set self-reported1.741
- gen_len on wmt16test set self-reported18.228
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Lvxue/finetuned-mt5-small-10epoch")