---
base_model: mor40/BulBERT-finetuned-cinexio
tags:
- generated_from_trainer
datasets:
- bgglue
metrics:
- accuracy
model-index:
- name: BulBERT-cinexio-10epochs
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: bgglue
      type: bgglue
      config: cinexio
      split: validation
      args: cinexio
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6288532675709001
---

<!-- 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. -->

# BulBERT-cinexio-10epochs

This model is a fine-tuned version of [mor40/BulBERT-finetuned-cinexio](https://huggingface.co/mor40/BulBERT-finetuned-cinexio) on the bgglue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1866
- Accuracy: 0.6289

## 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: 128
- eval_batch_size: 128
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 64   | 1.3334          | 0.5746   |
| No log        | 2.0   | 128  | 1.2053          | 0.6017   |
| No log        | 3.0   | 192  | 1.1826          | 0.6227   |
| No log        | 4.0   | 256  | 1.1826          | 0.6252   |
| No log        | 5.0   | 320  | 1.1671          | 0.6227   |
| No log        | 6.0   | 384  | 1.1743          | 0.6289   |
| No log        | 7.0   | 448  | 1.1795          | 0.6375   |
| 1.0262        | 8.0   | 512  | 1.1847          | 0.6178   |
| 1.0262        | 9.0   | 576  | 1.1877          | 0.6264   |
| 1.0262        | 10.0  | 640  | 1.1866          | 0.6289   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1