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gendered_man_woman
samzirbo/gendered_man_woman
gendered_man_woman 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 11, 2024
- Updated
- May 11, 2024
- SHA
- 134325da
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_man
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: 1.1748
- Bleu: 43.9515
- Meteor: 0.6913
- Chrf++: 62.7752
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++ |
|---|---|---|---|---|---|---|
| 4.3337 | 0.26 | 2500 | 2.0225 | 27.9199 | 0.5539 | 49.0346 |
| 2.4254 | 0.53 | 5000 | 1.7244 | 33.3111 | 0.6023 | 54.0561 |
| 2.1742 | 0.79 | 7500 | 1.5831 | 35.9048 | 0.6263 | 56.4407 |
| 2.027 | 1.05 | 10000 | 1.5000 | 37.665 | 0.6418 | 57.9131 |
| 1.9113 | 1.32 | 12500 | 1.4375 | 38.1525 | 0.6462 | 58.1999 |
| 1.8536 | 1.58 | 15000 | 1.3846 | 39.6031 | 0.659 | 59.4201 |
| 1.8003 | 1.84 | 17500 | 1.3468 | 40.1249 | 0.6625 | 59.8142 |
| 1.7367 | 2.11 | 20000 | 1.3078 | 41.024 | 0.6678 | 60.4354 |
| 1.6845 | 2.37 | 22500 | 1.2849 | 41.5369 | 0.6721 | 60.9458 |
| 1.6609 | 2.64 | 25000 | 1.2589 | 41.9956 | 0.676 | 61.2321 |
| 1.6362 | 2.9 | 27500 | 1.2358 | 42.5127 | 0.6817 | 61.7016 |
| 1.5945 | 3.16 | 30000 | 1.2218 | 42.7584 | 0.6816 | 61.8378 |
| 1.5638 | 3.43 | 32500 | 1.2088 | 42.9875 | 0.6844 | 62.0687 |
| 1.5557 | 3.69 | 35000 | 1.1983 | 43.3948 | 0.6862 | 62.2546 |
| 1.5469 | 3.95 | 37500 | 1.1864 | 43.5866 | 0.6877 | 62.5001 |
| 1.5151 | 4.22 | 40000 | 1.1826 | 43.5886 | 0.6888 | 62.501 |
| 1.5081 | 4.48 | 42500 | 1.1783 | 43.8291 | 0.6898 | 62.6281 |
| 1.5035 | 4.74 | 45000 | 1.1764 | 43.7796 | 0.6904 | 62.6856 |
| 1.4997 | 5.01 | 47500 | 1.1752 | 43.8886 | 0.6908 | 62.7218 |
| 1.4894 | 5.27 | 50000 | 1.1748 | 43.9515 | 0.6913 | 62.7752 |
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 11, 2024
- Updated
- May 11, 2024