metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: slurp-slot_baseline-xlm_r-en
results: []
slurp-slot_baseline-xlm_r-en
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3263
- Precision: 0.8145
- Recall: 0.8641
- F1: 0.8386
- Accuracy: 0.9341
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.1437 | 1.0 | 720 | 0.5236 | 0.6852 | 0.6623 | 0.6736 | 0.8860 |
| 0.5761 | 2.0 | 1440 | 0.3668 | 0.7348 | 0.7829 | 0.7581 | 0.9119 |
| 0.3087 | 3.0 | 2160 | 0.2996 | 0.7925 | 0.8280 | 0.8099 | 0.9270 |
| 0.2631 | 4.0 | 2880 | 0.2959 | 0.7872 | 0.8487 | 0.8168 | 0.9275 |
| 0.1847 | 5.0 | 3600 | 0.3121 | 0.7929 | 0.8373 | 0.8145 | 0.9290 |
| 0.1518 | 6.0 | 4320 | 0.3117 | 0.8080 | 0.8601 | 0.8332 | 0.9329 |
| 0.1232 | 7.0 | 5040 | 0.3153 | 0.7961 | 0.8490 | 0.8217 | 0.9267 |
| 0.0994 | 8.0 | 5760 | 0.3125 | 0.8105 | 0.8570 | 0.8331 | 0.9332 |
| 0.0968 | 9.0 | 6480 | 0.3242 | 0.8147 | 0.8637 | 0.8385 | 0.9329 |
| 0.0772 | 10.0 | 7200 | 0.3263 | 0.8145 | 0.8641 | 0.8386 | 0.9341 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3