metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-800abstracts
results: []
bert-800abstracts
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2845
- Precision: 0.6957
- Recall: 0.7694
- F1: 0.7307
- Accuracy: 0.9111
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 62 | 0.5356 | 0.4941 | 0.5665 | 0.5279 | 0.8374 |
| No log | 2.0 | 124 | 0.3440 | 0.6492 | 0.7011 | 0.6741 | 0.8950 |
| No log | 3.0 | 186 | 0.3010 | 0.6713 | 0.7640 | 0.7146 | 0.9064 |
| No log | 4.0 | 248 | 0.2845 | 0.6957 | 0.7694 | 0.7307 | 0.9111 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1