sbert_large-finetuned-sent_in_news_sents_3lab
This model is a fine-tuned version of sberbank-ai/sbert_large_nlu_ru on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9443
- Accuracy: 0.8580
- F1: 0.6199
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 17
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 264 | 0.6137 | 0.8608 | 0.3084 |
0.524 | 2.0 | 528 | 0.6563 | 0.8722 | 0.4861 |
0.524 | 3.0 | 792 | 0.7110 | 0.8494 | 0.4687 |
0.2225 | 4.0 | 1056 | 0.7323 | 0.8608 | 0.6015 |
0.2225 | 5.0 | 1320 | 0.9604 | 0.8551 | 0.6185 |
0.1037 | 6.0 | 1584 | 0.8801 | 0.8523 | 0.5535 |
0.1037 | 7.0 | 1848 | 0.9443 | 0.8580 | 0.6199 |
0.0479 | 8.0 | 2112 | 1.0048 | 0.8608 | 0.6168 |
0.0479 | 9.0 | 2376 | 0.9757 | 0.8551 | 0.6097 |
0.0353 | 10.0 | 2640 | 1.0743 | 0.8580 | 0.6071 |
0.0353 | 11.0 | 2904 | 1.1216 | 0.8580 | 0.6011 |
Framework versions
- Transformers 4.11.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
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