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gendered_balanced
samzirbo/gendered_balanced
gendered_balanced is a machine learning model from samzirbo. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- mt5
- Access
- Public
- Created
- May 7, 2024
- Updated
- May 7, 2024
- SHA
- a3ed1056
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. -->
gendered_balanced
This model is a fine-tuned version of samzirbo/mT5.en-es.pretrained on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1770
- Bleu: 43.8724
- Meteor: 0.6916
- Chrf++: 62.661
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- training_steps: 50000
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Chrf++ |
|---|---|---|---|---|---|---|
| 4.3102 | 0.44 | 2500 | 2.0045 | 27.8405 | 0.5556 | 49.2062 |
| 2.408 | 0.88 | 5000 | 1.7104 | 33.3638 | 0.6039 | 54.2966 |
| 2.1298 | 1.31 | 7500 | 1.5654 | 36.5253 | 0.6312 | 56.719 |
| 1.9966 | 1.75 | 10000 | 1.4823 | 37.7206 | 0.6409 | 57.8933 |
| 1.8882 | 2.19 | 12500 | 1.4168 | 39.2333 | 0.6518 | 59.0052 |
| 1.8055 | 2.63 | 15000 | 1.3736 | 39.9916 | 0.6585 | 59.5057 |
| 1.756 | 3.06 | 17500 | 1.3454 | 40.4973 | 0.6622 | 59.9928 |
| 1.6829 | 3.5 | 20000 | 1.3109 | 41.6502 | 0.6732 | 60.8574 |
| 1.6575 | 3.94 | 22500 | 1.2729 | 41.7069 | 0.6729 | 60.9659 |
| 1.5944 | 4.38 | 25000 | 1.2549 | 42.2762 | 0.6783 | 61.5535 |
| 1.5758 | 4.81 | 27500 | 1.2349 | 42.6516 | 0.6803 | 61.6749 |
| 1.5407 | 5.25 | 30000 | 1.2231 | 42.6637 | 0.6817 | 61.7779 |
| 1.5146 | 5.69 | 32500 | 1.2082 | 42.8507 | 0.6856 | 61.9916 |
| 1.4953 | 6.13 | 35000 | 1.1988 | 43.387 | 0.6873 | 62.2332 |
| 1.4687 | 6.56 | 37500 | 1.1874 | 43.4174 | 0.6876 | 62.3151 |
| 1.4664 | 7.0 | 40000 | 1.1825 | 43.7501 | 0.6913 | 62.5472 |
| 1.4415 | 7.44 | 42500 | 1.1803 | 43.7744 | 0.6909 | 62.6208 |
| 1.4408 | 7.88 | 45000 | 1.1771 | 43.8914 | 0.692 | 62.6599 |
| 1.4346 | 8.31 | 47500 | 1.1772 | 43.9709 | 0.6919 | 62.7096 |
| 1.4311 | 8.75 | 50000 | 1.1770 | 43.8724 | 0.6916 | 62.661 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2
- Library
- transformers
- Type
- mt5
- Created
- May 7, 2024
- Updated
- May 7, 2024