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gec_Ae_yanArt
mika5883/gec_Ae_yanArt
gec_Ae_yanArt is a machine learning model from mika5883. 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
- t5
- Access
- Public
- Created
- May 19, 2025
- Updated
- May 19, 2025
- SHA
- 56061b35
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. -->
gec_Ae_yanArt
This model is a fine-tuned version of mika5883/pretrain_rugec_msu on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2308
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: 3.83229e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 900
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3326 | 0.2250 | 100 | 0.2250 |
| 0.2006 | 0.4499 | 200 | 0.2117 |
| 0.1834 | 0.6749 | 300 | 0.2111 |
| 0.1744 | 0.8999 | 400 | 0.2038 |
| 0.1611 | 1.1237 | 500 | 0.2103 |
| 0.1477 | 1.3487 | 600 | 0.2075 |
| 0.1443 | 1.5737 | 700 | 0.2074 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.21.0
- Library
- transformers
- Type
- t5
- Created
- May 19, 2025
- Updated
- May 19, 2025