| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: kin-sentiC |
| 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. --> |
|
|
| # kin-sentiC |
|
|
| This model is a fine-tuned version of [RogerB/afro-xlmr-large-finetuned-kintweetsD](https://huggingface.co/RogerB/afro-xlmr-large-finetuned-kintweetsD) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8401 |
| - F1: 0.7066 |
|
|
| ## Model description |
|
|
| The model was trained and evaluated on a Kinyarwanda sentiment analysis dataset of tweets created by [Muhammad et al](https://huggingface.co/datasets/shmuhammad/AfriSenti-twitter-sentiment/viewer/kin). |
| It classifies Kinyarwanda sentences into three categories: positive (0), neutral (1), and negative (2). |
|
|
| ## Intended uses & limitations |
|
|
| The model is specifically designed for classifying Kinyarwanda sentences, with a focus on Kinyarwanda tweets. |
|
|
| ## Training and evaluation data |
|
|
| The training data used for training the model were a combination of the [train set from Muhammad et al](https://huggingface.co/datasets/shmuhammad/AfriSenti-twitter-sentiment/viewer/kin/train) and the [val set from Muhammad et al](https://huggingface.co/datasets/shmuhammad/AfriSenti-twitter-sentiment/viewer/kin/) , which served as the validation data during the training process. |
| For evaluating the model's performance, the test data used were sourced from the [test set from Muhammad et al](https://huggingface.co/datasets/shmuhammad/AfriSenti-twitter-sentiment/viewer/kin/test) |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-06 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 100000 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.913 | 1.0 | 1013 | 0.6933 | 0.7054 | |
| | 0.737 | 2.0 | 2026 | 0.5614 | 0.7854 | |
| | 0.646 | 3.0 | 3039 | 0.5357 | 0.8039 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
