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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
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