Edit model card

arabert_baseline_vocabulary_task3_fold1

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2325
  • Qwk: 0.2857
  • Mse: 0.2437

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Qwk Mse
No log 0.6667 2 3.6484 0.0328 3.6411
No log 1.3333 4 1.3150 0.0541 1.3226
No log 2.0 6 0.2810 0.0 0.2941
No log 2.6667 8 0.2059 0.0 0.2199
No log 3.3333 10 0.2435 0.0 0.2582
No log 4.0 12 0.2557 0.0 0.2715
No log 4.6667 14 0.2138 0.0 0.2290
No log 5.3333 16 0.2031 0.0 0.2168
No log 6.0 18 0.2284 0.0 0.2412
No log 6.6667 20 0.2060 0.2857 0.2178
No log 7.3333 22 0.2168 0.2857 0.2280
No log 8.0 24 0.2244 0.2857 0.2354
No log 8.6667 26 0.2313 0.2857 0.2422
No log 9.3333 28 0.2311 0.2857 0.2422
No log 10.0 30 0.2325 0.2857 0.2437

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1
Downloads last month
0
Safetensors
Model size
135M params
Tensor type
F32
·
Inference API
Unable to determine this model's library. Check the docs .

Model tree for salbatarni/arabert_baseline_vocabulary_task3_fold1

Finetuned
(424)
this model