Translation
Transformers
PyTorch
Safetensors
English
Toki Pona
multilingual
marian
text2text-generation
Generated from Trainer
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("ckb/en-toki-mt")
model = AutoModelForSeq2SeqLM.from_pretrained("ckb/en-toki-mt")Quick Links
en-toki-mt
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ROMANCE on the English - toki pona translation dataset on Tatoeba.
Model description
toki pona is a minimalist constructed language created in 2014 by Sonja Lang. The language features a very small volcabulary (~130 words) and a very simple grammar structure.
Intended uses & limitations
This model aims to translate English to Toki pona.
Training and evaluation data
The training data is acquired from all En-Toki sentence pairs on Tatoeba (~20000 pairs), without any filtering. Since this dataset mostly only includes core words (pu), it may produce inaccurate results when encountering more complex words. The model achieved a BLEU score of 54 on the testing set.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1
- Downloads last month
- 11
Model tree for ckb/en-toki-mt
Base model
Helsinki-NLP/opus-mt-en-ROMANCE
# 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="ckb/en-toki-mt")