metadata
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
results: []
ewc_stabilised
This model is a fine-tuned version of masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1396
- F1: 0.8317
- Precision: 0.8305
- Recall: 0.8328
- Accuracy: 0.9605
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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3184 | 0.9993 | 701 | 0.1480 | 0.7895 | 0.7950 | 0.7841 | 0.9511 |
| 0.1333 | 2.0 | 1403 | 0.1271 | 0.8195 | 0.8148 | 0.8242 | 0.9578 |
| 0.0975 | 2.9993 | 2104 | 0.1241 | 0.8289 | 0.8254 | 0.8324 | 0.9598 |
| 0.0744 | 4.0 | 2806 | 0.1293 | 0.8307 | 0.8313 | 0.8300 | 0.9603 |
| 0.0596 | 4.9964 | 3505 | 0.1396 | 0.8317 | 0.8305 | 0.8328 | 0.9605 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1