---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2-cawikitc
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: p1
  results: []
pipeline_tag: zero-shot-classification
---

<!-- 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. -->

# p1

This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cawikitc](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cawikitc) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8254
- Accuracy: 0.5
- Precision: 0.25
- Recall: 0.5
- F1: 0.3333
- Ratio: 1.0

## 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: 2
- seed: 47
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- lr_scheduler_warmup_steps: 4
- num_epochs: 2
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| 0.8263        | 0.38  | 10   | 0.8199          | 0.5      | 0.5       | 0.5    | 0.3473 | 0.0163 |
| 0.8283        | 0.75  | 20   | 0.8389          | 0.5      | 0.25      | 0.5    | 0.3333 | 1.0    |
| 0.8167        | 1.13  | 30   | 0.8325          | 0.5      | 0.25      | 0.5    | 0.3333 | 1.0    |
| 0.8183        | 1.51  | 40   | 0.8228          | 0.4973   | 0.2493    | 0.4973 | 0.3321 | 0.9973 |
| 0.8178        | 1.89  | 50   | 0.8254          | 0.5      | 0.25      | 0.5    | 0.3333 | 1.0    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2