---
license: afl-3.0
base_model: masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: ewc_stabilised_no_date_lambda0.4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ewc_stabilised_no_date_lambda0.4

This model is a fine-tuned version of [masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0](https://huggingface.co/masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1841
- F1: 0.8384
- Precision: 0.8348
- Recall: 0.8421
- Accuracy: 0.9649

## 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: 16
- eval_batch_size: 8
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
| 0.3292        | 0.9993 | 701  | 0.1360          | 0.7966 | 0.7971    | 0.7961 | 0.9564   |
| 0.1207        | 2.0    | 1403 | 0.1172          | 0.8235 | 0.8146    | 0.8326 | 0.9623   |
| 0.0891        | 2.9993 | 2104 | 0.1133          | 0.8348 | 0.8307    | 0.8390 | 0.9640   |
| 0.0684        | 4.0    | 2806 | 0.1172          | 0.8386 | 0.8411    | 0.8362 | 0.9650   |
| 0.0527        | 4.9993 | 3507 | 0.1268          | 0.8371 | 0.8302    | 0.8441 | 0.9645   |
| 0.0414        | 6.0    | 4209 | 0.1425          | 0.8390 | 0.8329    | 0.8453 | 0.9649   |
| 0.0329        | 6.9993 | 4910 | 0.1532          | 0.8385 | 0.8374    | 0.8396 | 0.9647   |
| 0.0263        | 8.0    | 5612 | 0.1650          | 0.8359 | 0.8287    | 0.8433 | 0.9645   |
| 0.0222        | 8.9993 | 6313 | 0.1793          | 0.8396 | 0.8398    | 0.8395 | 0.9652   |
| 0.019         | 9.9929 | 7010 | 0.1841          | 0.8384 | 0.8348    | 0.8421 | 0.9649   |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1