---
library_name: transformers
base_model: castorini/afriberta_base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: afriberta-stl-base-sentiment
  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. -->

# afriberta-stl-base-sentiment

This model is a fine-tuned version of [castorini/afriberta_base](https://huggingface.co/castorini/afriberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8213
- Sentiment Precision: 0.7191
- Sentiment Recall: 0.7099
- F1: 0.7111
- Sentiment Acc: 0.7161

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Sentiment Precision | Sentiment Recall | F1     | Sentiment Acc |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------:|:-------------:|
| 0.7579        | 1.0   | 402  | 0.7556          | 0.6904              | 0.6818           | 0.6729 | 0.6845        |
| 0.6418        | 2.0   | 804  | 0.7293          | 0.6981              | 0.6946           | 0.6945 | 0.7032        |
| 0.4884        | 3.0   | 1206 | 0.7908          | 0.6974              | 0.6863           | 0.6763 | 0.6933        |
| 0.3494        | 4.0   | 1608 | 0.8595          | 0.7064              | 0.6959           | 0.6971 | 0.7032        |
| 0.3035        | 5.0   | 2010 | 0.9201          | 0.7120              | 0.7062           | 0.7074 | 0.7120        |
| 0.2468        | 6.0   | 2412 | 0.9231          | 0.7012              | 0.6990           | 0.6996 | 0.7057        |


### Framework versions

- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2