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finetune_t5_small_gazeta_full
rhythm00/finetune_t5_small_gazeta_full
finetune_t5_small_gazeta_full is a machine learning model from rhythm00. 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. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- mt5
- Access
- Public
- Created
- Dec 23, 2023
- Updated
- Dec 23, 2023
- SHA
- a4e48f8d
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. -->
finetune_t5_small_gusev_full
This model is a fine-tuned version of cointegrated/rut5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7795
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: 0.0004
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 12
- total_train_batch_size: 288
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7388 | 0.61 | 150 | 2.2027 |
| 2.5562 | 1.22 | 300 | 2.0326 |
| 2.4982 | 1.83 | 450 | 1.9607 |
| 2.4324 | 2.44 | 600 | 1.9077 |
| 2.4015 | 3.05 | 750 | 1.8711 |
| 2.3623 | 3.65 | 900 | 1.8451 |
| 2.3282 | 4.26 | 1050 | 1.8304 |
| 2.3072 | 4.87 | 1200 | 1.8120 |
| 2.2878 | 5.48 | 1350 | 1.8007 |
| 2.2689 | 6.09 | 1500 | 1.7919 |
| 2.2814 | 6.7 | 1650 | 1.7863 |
| 2.2443 | 7.31 | 1800 | 1.7835 |
| 2.2665 | 7.92 | 1950 | 1.7795 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- mt5
- License
- mit
- Created
- Dec 23, 2023
- Updated
- Dec 23, 2023