metadata
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: damage_trigger_effect_2023-10-06_11_33
results: []
damage_trigger_effect_2023-10-06_11_33
This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3069
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9128
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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 28 | 0.3496 | 0.0 | 0.0 | 0.0 | 0.9016 |
| No log | 2.0 | 56 | 0.2948 | 0.0 | 0.0 | 0.0 | 0.9147 |
| No log | 3.0 | 84 | 0.2590 | 0.0 | 0.0 | 0.0 | 0.9171 |
| No log | 4.0 | 112 | 0.2689 | 0.0 | 0.0 | 0.0 | 0.9078 |
| No log | 5.0 | 140 | 0.2561 | 0.0 | 0.0 | 0.0 | 0.9101 |
| No log | 6.0 | 168 | 0.2447 | 0.0 | 0.0 | 0.0 | 0.9155 |
| No log | 7.0 | 196 | 0.2621 | 0.0 | 0.0 | 0.0 | 0.9085 |
| No log | 8.0 | 224 | 0.2734 | 0.0 | 0.0 | 0.0 | 0.9143 |
| No log | 9.0 | 252 | 0.2806 | 0.0 | 0.0 | 0.0 | 0.9066 |
| No log | 10.0 | 280 | 0.2954 | 0.0 | 0.0 | 0.0 | 0.9105 |
| No log | 11.0 | 308 | 0.2929 | 0.0 | 0.0 | 0.0 | 0.9128 |
| No log | 12.0 | 336 | 0.2936 | 0.0 | 0.0 | 0.0 | 0.9116 |
| No log | 13.0 | 364 | 0.2948 | 0.0 | 0.0 | 0.0 | 0.9132 |
| No log | 14.0 | 392 | 0.2973 | 0.0 | 0.0 | 0.0 | 0.9151 |
| No log | 15.0 | 420 | 0.3069 | 0.0 | 0.0 | 0.0 | 0.9128 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0