transformers safetensors bert text-classification generated_from_trainer dataset:basque_glue base_model:ixa-ehu/berteus-base-cased base_model:finetune:ixa-ehu/berteus-base-cased model-index autotrain_compatible endpoints_compatible region:us
---
base_model: ixa-ehu/berteus-base-cased
datasets:
- basque_glue
library_name: transformers
metrics:
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: doku-berteus
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: basque_glue
      type: basque_glue
      config: bhtc
      split: validation
      args: bhtc
    metrics:
    - type: precision
      value: 0.7745415318230853
      name: Precision
    - type: recall
      value: 0.7745415318230853
      name: Recall
---

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# doku-berteus

This model is a fine-tuned version of [ixa-ehu/berteus-base-cased](https://huggingface.co/ixa-ehu/berteus-base-cased) on the basque_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7077
- Micro F1: 0.7745
- Precision: 0.7745
- Recall: 0.7745
- F1 Class 0: 0.7290
- F1 Class 1: 0.2857
- F1 Class 2: 0.8256
- F1 Class 3: 0.7758
- F1 Class 4: 0.7534
- F1 Class 5: 0.8409
- F1 Class 6: 0.5378
- F1 Class 7: 0.375
- F1 Class 8: 0.8333
- F1 Class 9: 0.7769
- F1 Class 10: 0.8136
- F1 Class 11: 0.1538

## 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: 16
- eval_batch_size: 16
- seed: 1
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Micro F1 | Precision | Recall | F1 Class 0 | F1 Class 1 | F1 Class 2 | F1 Class 3 | F1 Class 4 | F1 Class 5 | F1 Class 6 | F1 Class 7 | F1 Class 8 | F1 Class 9 | F1 Class 10 | F1 Class 11 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:-----------:|:-----------:|
| 0.8177        | 1.0   | 537  | 0.8337          | 0.7458   | 0.7458    | 0.7458 | 0.6906     | 0.0        | 0.8304     | 0.7453     | 0.6777     | 0.8086     | 0.4685     | 0.4828     | 0.8272     | 0.7709     | 0.7788      | 0.0         |
| 0.5226        | 2.0   | 1074 | 0.8253          | 0.7534   | 0.7534    | 0.7534 | 0.7152     | 0.08       | 0.8302     | 0.7599     | 0.6620     | 0.8278     | 0.5113     | 0.4706     | 0.8280     | 0.7826     | 0.7698      | 0.2727      |
| 0.3745        | 3.0   | 1611 | 0.9744          | 0.7458   | 0.7458    | 0.7458 | 0.7262     | 0.0714     | 0.7946     | 0.7526     | 0.6929     | 0.7967     | 0.5312     | 0.5574     | 0.8232     | 0.7449     | 0.7758      | 0.4615      |
| 0.1982        | 4.0   | 2148 | 1.1651          | 0.7518   | 0.7518    | 0.7518 | 0.7099     | 0.2069     | 0.8145     | 0.7632     | 0.6719     | 0.7911     | 0.5138     | 0.4898     | 0.8473     | 0.7560     | 0.7751      | 0.3704      |
| 0.0823        | 5.0   | 2685 | 1.4201          | 0.7421   | 0.7421    | 0.7421 | 0.6981     | 0.2286     | 0.8128     | 0.7428     | 0.6772     | 0.7884     | 0.5484     | 0.5185     | 0.8412     | 0.7692     | 0.7593      | 0.2609      |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0
