metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: distilcamembert-cae-territory
results: []
distilcamembert-cae-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: 0.7346
- Precision: 0.7139
- Recall: 0.6835
- F1: 0.6887
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 |
|---|---|---|---|---|---|---|
| 1.1749 | 1.0 | 40 | 1.0498 | 0.1963 | 0.4430 | 0.2720 |
| 0.9833 | 2.0 | 80 | 0.8853 | 0.7288 | 0.6709 | 0.6625 |
| 0.6263 | 3.0 | 120 | 0.7503 | 0.7237 | 0.6709 | 0.6689 |
| 0.3563 | 4.0 | 160 | 0.7346 | 0.7139 | 0.6835 | 0.6887 |
| 0.2253 | 5.0 | 200 | 0.7303 | 0.7139 | 0.6835 | 0.6887 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2