rubert-base-cased-finetuned-mnli
This model is a fine-tuned version of DeepPavlov/rubert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9008
- Accuracy: 0.7575
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: 0.0002
- 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: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8474 | 1.0 | 6171 | 0.8942 | 0.7575 |
| 0.8348 | 2.0 | 12342 | 0.9008 | 0.7575 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.13.3
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