metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: distilcamembert-cae-all
results: []
distilcamembert-cae-all
This model is a fine-tuned version of cmarkea/distilcamembert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6016
- Precision: 0.8510
- Recall: 0.8481
- F1: 0.8471
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 1.18 | 1.0 | 40 | 0.9901 | 0.6418 | 0.4557 | 0.2991 |
| 0.8718 | 2.0 | 80 | 0.6938 | 0.7667 | 0.7468 | 0.7196 |
| 0.4656 | 3.0 | 120 | 0.6928 | 0.8364 | 0.8354 | 0.8353 |
| 0.2418 | 4.0 | 160 | 0.6008 | 0.8276 | 0.8228 | 0.8228 |
| 0.1285 | 5.0 | 200 | 0.6016 | 0.8510 | 0.8481 | 0.8471 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2