---
library_name: transformers
license: mit
base_model: Davlan/afro-xlmr-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: afroxlmr-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. -->

# afroxlmr-stl-base-sentiment

This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7492
- Sentiment Precision: 0.7270
- Sentiment Recall: 0.7267
- F1: 0.7268
- Sentiment Acc: 0.7319

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------:|:-------------:|
| 0.7555        | 1.0   | 402  | 0.6987          | 0.7053              | 0.7024           | 0.6975 | 0.7045        |
| 0.6743        | 2.0   | 804  | 0.6671          | 0.7238              | 0.7210           | 0.7217 | 0.7269        |
| 0.5465        | 3.0   | 1206 | 0.7184          | 0.7266              | 0.7119           | 0.6993 | 0.7182        |
| 0.4515        | 4.0   | 1608 | 0.7143          | 0.7348              | 0.7272           | 0.7279 | 0.7294        |
| 0.4107        | 5.0   | 2010 | 0.7514          | 0.7219              | 0.7187           | 0.7194 | 0.7257        |
| 0.4057        | 6.0   | 2412 | 0.7492          | 0.7270              | 0.7267           | 0.7268 | 0.7319        |


### Framework versions

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