File size: 2,409 Bytes
769c482 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
library_name: transformers
base_model: ai-forever/ruBert-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ruBert-large-topic_classification
results: []
---
<!-- 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. -->
# ruBert-large-topic_classification
This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7900
- Precision: 0.8793
- Recall: 0.8646
- F1: 0.8688
- Accuracy: 0.8824
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 44 | 0.6327 | 0.8534 | 0.7883 | 0.8046 | 0.8186 |
| No log | 2.0 | 88 | 0.4897 | 0.8847 | 0.8401 | 0.8548 | 0.8676 |
| No log | 3.0 | 132 | 0.5957 | 0.8732 | 0.8617 | 0.8638 | 0.8676 |
| No log | 4.0 | 176 | 0.6598 | 0.8808 | 0.8658 | 0.8700 | 0.8824 |
| No log | 5.0 | 220 | 0.7086 | 0.8705 | 0.8589 | 0.8625 | 0.8775 |
| No log | 6.0 | 264 | 0.7445 | 0.8793 | 0.8646 | 0.8688 | 0.8824 |
| No log | 7.0 | 308 | 0.7661 | 0.8793 | 0.8646 | 0.8688 | 0.8824 |
| No log | 8.0 | 352 | 0.7795 | 0.8793 | 0.8646 | 0.8688 | 0.8824 |
| No log | 9.0 | 396 | 0.7870 | 0.8793 | 0.8646 | 0.8688 | 0.8824 |
| No log | 10.0 | 440 | 0.7900 | 0.8793 | 0.8646 | 0.8688 | 0.8824 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|