metadata
license: apache-2.0
base_model: morten-j/Mehdie_Extended-mBERT
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: fine_tuned_emBERT
results: []
fine_tuned_emBERT
This model is a fine-tuned version of morten-j/Mehdie_Extended-mBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1441
- F1: 0.7568
- F5: 0.7196
- Precision: 0.875
- Recall: 0.6667
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 30 | 0.3540 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 60 | 0.2975 | 0.4348 | 0.4077 | 0.5263 | 0.3704 |
| No log | 3.0 | 90 | 0.3550 | 0.45 | 0.3969 | 0.6923 | 0.3333 |
| No log | 4.0 | 120 | 0.2962 | 0.5405 | 0.4598 | 1.0 | 0.3704 |
| No log | 5.0 | 150 | 0.2629 | 0.5909 | 0.5437 | 0.7647 | 0.4815 |
| No log | 6.0 | 180 | 0.2459 | 0.5778 | 0.5368 | 0.7222 | 0.4815 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2