metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
base_model: cmarkea/distilcamembert-base
model-index:
- name: distilcamembert-cae-no-territory
results: []
distilcamembert-cae-no-territory
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: 0.6885
- Precision: 0.7873
- Recall: 0.7848
- F1: 0.7855
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 |
|---|---|---|---|---|---|---|
| 1.1796 | 1.0 | 40 | 0.9743 | 0.5640 | 0.4937 | 0.3731 |
| 0.8788 | 2.0 | 80 | 0.8037 | 0.7438 | 0.6709 | 0.6472 |
| 0.4982 | 3.0 | 120 | 0.7692 | 0.8264 | 0.7089 | 0.7558 |
| 0.2865 | 4.0 | 160 | 0.7676 | 0.7498 | 0.7215 | 0.7192 |
| 0.1502 | 5.0 | 200 | 0.6885 | 0.7873 | 0.7848 | 0.7855 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2