---
library_name: transformers
license: mit
base_model: EthioNLP/EthioLLM-l-70K
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: ethiollm-stl-LLfinetuned-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. -->

# ethiollm-stl-LLfinetuned-sentiment

This model is a fine-tuned version of [EthioNLP/EthioLLM-l-70K](https://huggingface.co/EthioNLP/EthioLLM-l-70K) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8844
- Sentiment Precision: 0.7140
- Sentiment Recall: 0.7132
- F1: 0.7133
- Sentiment Acc: 0.7182

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------:|:-------------:|
| 0.9854        | 1.0   | 402  | 0.9077          | 0.6241              | 0.6073           | 0.6014 | 0.6010        |
| 0.7953        | 2.0   | 804  | 0.7370          | 0.6871              | 0.6833           | 0.6843 | 0.6895        |
| 0.6382        | 3.0   | 1206 | 0.8207          | 0.6923              | 0.6674           | 0.6492 | 0.6771        |
| 0.4706        | 4.0   | 1608 | 0.7923          | 0.7166              | 0.7063           | 0.7084 | 0.7132        |
| 0.3507        | 5.0   | 2010 | 0.8754          | 0.7055              | 0.7018           | 0.7028 | 0.7082        |
| 0.2955        | 6.0   | 2412 | 0.8844          | 0.7140              | 0.7132           | 0.7133 | 0.7182        |


### Framework versions

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