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iva_mt_wslot-m2m100_418M-en-zh
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: 0.0120
- Bleu: 69.4383
- Gen Len: 19.4038
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 |
|---|---|---|---|---|---|
| 0.0155 | 1.0 | 2109 | 0.0132 | 66.1893 | 19.117 |
| 0.011 | 2.0 | 4218 | 0.0120 | 66.5023 | 19.2003 |
| 0.0084 | 3.0 | 6327 | 0.0116 | 68.2038 | 19.4521 |
| 0.0061 | 4.0 | 8436 | 0.0115 | 69.129 | 19.2181 |
| 0.0046 | 5.0 | 10545 | 0.0117 | 69.3609 | 19.3212 |
| 0.0035 | 6.0 | 12654 | 0.0119 | 69.1841 | 19.3972 |
| 0.0028 | 7.0 | 14763 | 0.0120 | 69.4383 | 19.4038 |
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}
}
