mbert_trim_ende
该模型基于bert-base-multilingual-cased，使用TextPruner对词表进行裁剪，保留iwslt14德英数据集，用于测试bert-fused的翻译效果。 并且在iwslt14德英数据集上进行掩码语言模型微调，数据的拼接方式是： de, en, de[sep]en, en[sep]de。
Model Details
lang：德英 vocab_size: 119547 -> 21443 model_size: 682M -> 392M iwslt14 de_en BLEU: ?--- tags: - generated_from_trainer metrics: - accuracy model-index: - name: mbert_trim_ende results: []
mbert_trim_ende
This model is a fine-tuned version of miugod/mbert_trim_ende on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8260
- Accuracy: 0.8200
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3
- Downloads last month
- 4
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.