---
library_name: transformers
base_model: rasyosef/roberta-base-amharic
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: STL-rasyosef-roberta-base-amharic-sentiment-finetuned
  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. -->

# STL-rasyosef-roberta-base-amharic-sentiment-finetuned

This model is a fine-tuned version of [rasyosef/roberta-base-amharic](https://huggingface.co/rasyosef/roberta-base-amharic) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6921
- Sentiment Precision: 0.7152
- Sentiment Recall: 0.7136
- F1: 0.7134
- Sentiment Acc: 0.7219

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Sentiment Precision | Sentiment Recall | F1     | Sentiment Acc |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------:|:-------------:|
| 0.0767        | 1.0   | 377  | 1.4050          | 0.7211              | 0.6814           | 0.6774 | 0.6920        |
| 0.4186        | 2.0   | 754  | 0.7378          | 0.7331              | 0.7342           | 0.7332 | 0.7382        |
| 0.2453        | 3.0   | 1131 | 1.0265          | 0.7019              | 0.6915           | 0.6934 | 0.6983        |
| 0.1537        | 4.0   | 1508 | 1.4778          | 0.7365              | 0.7293           | 0.7293 | 0.7294        |
| 0.0941        | 5.0   | 1885 | 1.6921          | 0.7152              | 0.7136           | 0.7134 | 0.7219        |


### Framework versions

- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.23.1