---
library_name: transformers
license: mit
base_model: Davlan/afro-xlmr-large
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: cs221-afro-xlmr-large-amh-finetuned-20-epochs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cs221-afro-xlmr-large-amh-finetuned-20-epochs

This model is a fine-tuned version of [Davlan/afro-xlmr-large](https://huggingface.co./Davlan/afro-xlmr-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2541
- F1: 0.7241
- Roc Auc: 0.8299
- Accuracy: 0.5197

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch 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: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.4225        | 1.0   | 89   | 0.3527          | 0.3104 | 0.5903  | 0.2761   |
| 0.2896        | 2.0   | 178  | 0.2815          | 0.6194 | 0.7431  | 0.4606   |
| 0.2408        | 3.0   | 267  | 0.2444          | 0.7125 | 0.8140  | 0.5099   |
| 0.1923        | 4.0   | 356  | 0.2497          | 0.7108 | 0.8113  | 0.5296   |
| 0.1707        | 5.0   | 445  | 0.2541          | 0.7241 | 0.8299  | 0.5197   |
| 0.132         | 6.0   | 534  | 0.2664          | 0.7073 | 0.8155  | 0.5113   |
| 0.1004        | 7.0   | 623  | 0.2756          | 0.7183 | 0.8216  | 0.5211   |
| 0.0841        | 8.0   | 712  | 0.2846          | 0.7229 | 0.8291  | 0.5183   |
| 0.0719        | 9.0   | 801  | 0.2910          | 0.7225 | 0.8290  | 0.5155   |
| 0.0667        | 10.0  | 890  | 0.2898          | 0.7212 | 0.8268  | 0.5169   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0