|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# damage_trigger_effect_2023-10-06_11_33 |
|
|
|
This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/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 |
|
|