|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- iva_mt_wslot |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: iva_mt_wslot-m2m100_418M-zh-en |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: iva_mt_wslot |
|
type: iva_mt_wslot |
|
config: en-zh |
|
split: validation |
|
args: en-zh |
|
metrics: |
|
- name: Bleu |
|
type: bleu |
|
value: 67.9385 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# iva_mt_wslot-m2m100_418M-zh-en |
|
|
|
This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the iva_mt_wslot dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0139 |
|
- Bleu: 67.9385 |
|
- Gen Len: 18.9988 |
|
|
|
## 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: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
|
| 0.016 | 1.0 | 2437 | 0.0138 | 62.077 | 18.6077 | |
|
| 0.0114 | 2.0 | 4874 | 0.0126 | 64.3834 | 18.9019 | |
|
| 0.0084 | 3.0 | 7311 | 0.0123 | 66.0012 | 18.9206 | |
|
| 0.0067 | 4.0 | 9748 | 0.0123 | 66.7838 | 19.0018 | |
|
| 0.005 | 5.0 | 12185 | 0.0124 | 66.9053 | 18.9527 | |
|
| 0.0039 | 6.0 | 14622 | 0.0128 | 67.5252 | 18.9918 | |
|
| 0.003 | 7.0 | 17059 | 0.0131 | 67.3664 | 18.9609 | |
|
| 0.0025 | 8.0 | 19496 | 0.0135 | 67.792 | 19.0198 | |
|
| 0.0019 | 9.0 | 21933 | 0.0137 | 67.7256 | 18.9591 | |
|
| 0.0015 | 10.0 | 24370 | 0.0139 | 67.9385 | 18.9988 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.1 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.13.3 |
|
|
