metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: my_awesome_model
results: []
my_awesome_model
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4723
- Accuracy: {'accuracy': 0.5292066259808196}
- Precision: {'precision': 0.5270248196529665}
- Recall: {'recall': 0.5128581630410899}
- F1: {'f1': 0.4836938691814141}
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 2.3362 | 1.0 | 1390 | 1.8634 | {'accuracy': 0.4119442022667829} | {'precision': 0.3707812573639524} | {'recall': 0.39448170731707316} | {'f1': 0.33817627082664936} |
| 1.5346 | 2.0 | 2780 | 1.4723 | {'accuracy': 0.5292066259808196} | {'precision': 0.5270248196529665} | {'recall': 0.5128581630410899} | {'f1': 0.4836938691814141} |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1