metadata
license: apache-2.0
base_model: PartAI/TookaBERT-Base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_model
results: []
my_model
This model is a fine-tuned version of PartAI/TookaBERT-Base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9495
- Precision: 0.5098
- Recall: 0.4866
- F1: 0.4979
- Accuracy: 0.8050
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 10 | 1.4199 | 0.3919 | 0.3102 | 0.3463 | 0.7206 |
| No log | 2.0 | 20 | 1.2065 | 0.4497 | 0.3824 | 0.4133 | 0.7573 |
| No log | 3.0 | 30 | 1.0512 | 0.4792 | 0.4305 | 0.4535 | 0.7759 |
| No log | 4.0 | 40 | 0.9780 | 0.5056 | 0.4840 | 0.4945 | 0.8022 |
| No log | 5.0 | 50 | 0.9495 | 0.5098 | 0.4866 | 0.4979 | 0.8050 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1