metadata
library_name: transformers
license: mit
base_model: almanach/camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-small-paragraph-classifier
results: []
bert-small-paragraph-classifier
This model is a fine-tuned version of almanach/camembert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1045
- Accuracy: 0.9983
- Precision: 0.9983
- Recall: 0.9983
- F1: 0.9983
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 338 | 0.1045 | 0.9983 | 0.9983 | 0.9983 | 0.9983 |
| 0.4417 | 2.0 | 676 | 0.0408 | 0.9983 | 0.9983 | 0.9983 | 0.9983 |
| 0.0461 | 3.0 | 1014 | 0.0291 | 0.9983 | 0.9983 | 0.9983 | 0.9983 |
Framework versions
- Transformers 4.53.1
- Pytorch 2.7.1
- Datasets 3.6.0
- Tokenizers 0.21.2