Translation
Transformers
TensorBoard
Safetensors
marian
text2text-generation
Generated from Trainer
Eval Results (legacy)
# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM
tokenizer = AutoTokenizer.from_pretrained("sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en")
model = AutoModelForMultimodalLM.from_pretrained("sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en")Quick Links
opus-mt-ca-en-ft-kde4-mt-ca-en
This model is a fine-tuned version of Helsinki-NLP/opus-mt-ca-en on the kde4 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5999
- Model Preparation Time: 0.0033
- Bleu: 67.6779
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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en
Base model
Helsinki-NLP/opus-mt-ca-enDataset used to train sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en
Evaluation results
- Bleu on kde4self-reported67.678
# 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="sauc-abadal-lloret/opus-mt-ca-en-ft-kde4-mt-ca-en")