---
tags:
- generated_from_trainer
datasets:
- rubric
metrics:
- accuracy
model-index:
- name: EstBERT128_Rubric
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: rubric
      type: rubric
      args: rubric
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8329238295555115
---

<!-- 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. -->

# EstBERT128_Rubric

This model is a fine-tuned version of [tartuNLP/EstBERT](https://huggingface.co/tartuNLP/EstBERT) on the rubric categories of the [Estonian Valence dataset](http://peeter.eki.ee:5000/valence/paragraphsquery).
It achieves the following results on the evaluation set:
- Loss: 2.0552
- Accuracy: 0.8329

## 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: 16
- seed: 3
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: polynomial
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1147        | 1.0   | 179   | 0.7421          | 0.7445   |
| 0.4323        | 2.0   | 358   | 0.6863          | 0.7813   |
| 0.1442        | 3.0   | 537   | 0.8545          | 0.7838   |
| 0.0496        | 4.0   | 716   | 1.2872          | 0.7494   |
| 0.0276        | 5.0   | 895   | 1.4702          | 0.7641   |
| 0.0202        | 6.0   | 1074  | 1.3764          | 0.7838   |
| 0.0144        | 7.0   | 1253  | 1.5762          | 0.7887   |
| 0.0078        | 8.0   | 1432  | 1.8806          | 0.7666   |
| 0.0177        | 9.0   | 1611  | 1.6159          | 0.7912   |
| 0.0223        | 10.0  | 1790  | 1.5863          | 0.7936   |
| 0.0108        | 11.0  | 1969  | 1.8051          | 0.7912   |
| 0.0201        | 12.0  | 2148  | 1.9344          | 0.7789   |
| 0.0252        | 13.0  | 2327  | 1.7978          | 0.8084   |
| 0.0104        | 14.0  | 2506  | 1.8779          | 0.7887   |
| 0.0138        | 15.0  | 2685  | 1.6456          | 0.8133   |
| 0.0066        | 16.0  | 2864  | 1.9668          | 0.7912   |
| 0.0148        | 17.0  | 3043  | 2.0068          | 0.7813   |
| 0.0128        | 18.0  | 3222  | 2.1539          | 0.7617   |
| 0.0115        | 19.0  | 3401  | 2.2490          | 0.7838   |
| 0.0186        | 20.0  | 3580  | 2.1768          | 0.7666   |
| 0.0051        | 21.0  | 3759  | 1.8859          | 0.7912   |
| 0.001         | 22.0  | 3938  | 2.0132          | 0.7912   |
| 0.0133        | 23.0  | 4117  | 1.8786          | 0.8084   |
| 0.0149        | 24.0  | 4296  | 2.2307          | 0.7961   |
| 0.014         | 25.0  | 4475  | 2.0041          | 0.8206   |
| 0.0132        | 26.0  | 4654  | 1.8872          | 0.8133   |
| 0.0079        | 27.0  | 4833  | 1.9357          | 0.7961   |
| 0.0078        | 28.0  | 5012  | 2.1891          | 0.7936   |
| 0.0126        | 29.0  | 5191  | 2.0207          | 0.8034   |
| 0.0003        | 30.0  | 5370  | 2.1917          | 0.8010   |
| 0.0015        | 31.0  | 5549  | 2.0417          | 0.8157   |
| 0.0056        | 32.0  | 5728  | 2.1172          | 0.8084   |
| 0.0058        | 33.0  | 5907  | 2.1921          | 0.8206   |
| 0.0001        | 34.0  | 6086  | 2.0079          | 0.8206   |
| 0.0031        | 35.0  | 6265  | 2.2447          | 0.8206   |
| 0.0007        | 36.0  | 6444  | 2.1802          | 0.8084   |
| 0.0061        | 37.0  | 6623  | 2.1103          | 0.8157   |
| 0.0           | 38.0  | 6802  | 2.2265          | 0.8084   |
| 0.0035        | 39.0  | 6981  | 2.0549          | 0.8329   |
| 0.0038        | 40.0  | 7160  | 2.1352          | 0.8182   |
| 0.0001        | 41.0  | 7339  | 2.0975          | 0.8108   |
| 0.0           | 42.0  | 7518  | 2.0833          | 0.8256   |
| 0.0           | 43.0  | 7697  | 2.1020          | 0.8280   |
| 0.0           | 44.0  | 7876  | 2.0841          | 0.8305   |
| 0.0           | 45.0  | 8055  | 2.2085          | 0.8182   |
| 0.0           | 46.0  | 8234  | 2.0756          | 0.8329   |
| 0.0           | 47.0  | 8413  | 2.1237          | 0.8305   |
| 0.0           | 48.0  | 8592  | 2.1217          | 0.8280   |
| 0.0052        | 49.0  | 8771  | 2.3567          | 0.8059   |
| 0.0014        | 50.0  | 8950  | 2.1710          | 0.8206   |
| 0.0032        | 51.0  | 9129  | 2.1452          | 0.8206   |
| 0.0           | 52.0  | 9308  | 2.2820          | 0.8133   |
| 0.0001        | 53.0  | 9487  | 2.2279          | 0.8157   |
| 0.0           | 54.0  | 9666  | 2.1841          | 0.8182   |
| 0.0           | 55.0  | 9845  | 2.1208          | 0.8231   |
| 0.0           | 56.0  | 10024 | 2.0967          | 0.8256   |
| 0.0002        | 57.0  | 10203 | 2.1911          | 0.8231   |
| 0.0           | 58.0  | 10382 | 2.2014          | 0.8231   |
| 0.0           | 59.0  | 10561 | 2.2014          | 0.8182   |


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.1+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3