metadata
license: mit
tags:
- generated_from_trainer
datasets:
- iva_mt_wslot
metrics:
- bleu
model-index:
- name: iva_mt_wslot-m2m100_418M-en-ja
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: iva_mt_wslot
type: iva_mt_wslot
config: en-ja
split: validation
args: en-ja
metrics:
- name: Bleu
type: bleu
value: 66.503
iva_mt_wslot-m2m100_418M-en-ja
This model is a fine-tuned version of facebook/m2m100_418M on the iva_mt_wslot dataset. It achieves the following results on the evaluation set:
- Loss: 0.0153
- Bleu: 66.503
- Gen Len: 20.9519
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
---|---|---|---|---|---|
0.0185 | 1.0 | 2017 | 0.0164 | 63.4304 | 20.6499 |
0.0134 | 2.0 | 4034 | 0.0150 | 64.827 | 20.666 |
0.0104 | 3.0 | 6051 | 0.0146 | 64.465 | 21.2155 |
0.0079 | 4.0 | 8068 | 0.0148 | 64.8578 | 20.7915 |
0.0062 | 5.0 | 10085 | 0.0149 | 65.9149 | 21.0718 |
0.005 | 6.0 | 12102 | 0.0151 | 66.2905 | 20.8766 |
0.004 | 7.0 | 14119 | 0.0153 | 66.503 | 20.9519 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
Citation
If you use this model, please cite the following:
@article{Sowanski2023SlotLI,
title={Slot Lost in Translation? Not Anymore: A Machine Translation Model for Virtual Assistants with Type-Independent Slot Transfer},
author={Marcin Sowanski and Artur Janicki},
journal={2023 30th International Conference on Systems, Signals and Image Processing (IWSSIP)},
year={2023},
pages={1-5}
}