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---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: distilcamembert-cae-no-territory
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilcamembert-cae-no-territory
This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/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
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