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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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