Downloads · 30 days
3
2% of all-time downloads
m2m100-A100-es-zap-data
josueu/m2m100-A100-es-zap-data
m2m100-A100-es-zap-data is a machine learning model from josueu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
170
Public
Parameters
484M
25.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.9 GB · 100%
At a glance
- Library
- transformers
- License
- mit
- Model type
- m2m_100
- Access
- Public
- Created
- Mar 28, 2026
- Updated
- Mar 28, 2026
- SHA
- c5693fc2
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
m2m100-A100-es-zap-data
This model is a fine-tuned version of facebook/m2m100_418M on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3220
- Bleu: 33.1219
- Ter: 51.8382
- Meteor: 0.5662
- Chrf: 57.4929
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Ter | Meteor | Chrf |
|---|---|---|---|---|---|---|---|
| 3.4807 | 1.0 | 81 | 1.9528 | 10.5771 | 75.3676 | 0.3663 | 37.5181 |
| 1.3969 | 2.0 | 162 | 1.5794 | 17.0487 | 62.8676 | 0.4594 | 45.3205 |
| 0.9809 | 3.0 | 243 | 1.2933 | 21.3958 | 59.4363 | 0.4789 | 48.8722 |
| 0.5687 | 4.0 | 324 | 1.2516 | 23.5237 | 59.5588 | 0.5025 | 51.5069 |
| 0.3665 | 5.0 | 405 | 1.2780 | 23.8626 | 68.0147 | 0.5298 | 52.4311 |
| 0.2579 | 6.0 | 486 | 1.2683 | 29.1979 | 56.9853 | 0.5391 | 54.3828 |
| 0.1656 | 7.0 | 567 | 1.2798 | 29.6347 | 54.2892 | 0.5397 | 54.8843 |
| 0.1348 | 8.0 | 648 | 1.2829 | 29.3764 | 54.5343 | 0.5451 | 55.6008 |
| 0.0884 | 9.0 | 729 | 1.2720 | 31.1738 | 52.4510 | 0.5651 | 56.4094 |
| 0.0774 | 10.0 | 810 | 1.2931 | 32.8888 | 52.2059 | 0.5692 | 57.6071 |
| 0.0545 | 11.0 | 891 | 1.3301 | 32.2780 | 53.1863 | 0.5715 | 56.1920 |
| 0.0387 | 12.0 | 972 | 1.3245 | 31.8118 | 53.4314 | 0.5602 | 56.7971 |
| 0.0288 | 13.0 | 1053 | 1.3220 | 33.1219 | 51.8382 | 0.5662 | 57.4929 |
Framework versions
- Transformers 5.4.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
- Library
- transformers
- Type
- m2m_100
- License
- mit
- Created
- Mar 28, 2026
- Updated
- Mar 28, 2026