metadata
tags:
- generated_from_trainer
datasets:
- xnli
metrics:
- accuracy
- f1
base_model: aubmindlab/bert-base-arabertv02
model-index:
- name: bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: xnli
type: xnli
config: ar
split: train
args: ar
metrics:
- type: accuracy
value: 0.767065868263473
name: Accuracy
- type: f1
value: 0.767539058869847
name: F1
bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the xnli dataset. It achieves the following results on the evaluation set:
- Loss: 0.5796
- Accuracy: 0.7671
- F1: 0.7675
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.5804 | 1.0 | 12271 | 0.5796 | 0.7671 | 0.7675 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2