metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: mrc-xlmr-base-dsc
results: []
mrc-xlmr-base-dsc
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7023
- Precision: 0.7109
- Recall: 0.6810
- F1: 0.6767
- Exact Match: 0.7123
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Exact Match |
|---|---|---|---|---|---|---|---|
| 0.7291 | 1.0 | 3180 | 0.6487 | 0.6459 | 0.5921 | 0.5958 | 0.6368 |
| 0.612 | 2.0 | 6360 | 0.5966 | 0.7004 | 0.6382 | 0.6449 | 0.6793 |
| 0.4627 | 3.0 | 9540 | 0.6061 | 0.6920 | 0.6645 | 0.6573 | 0.6949 |
| 0.3604 | 4.0 | 12720 | 0.6453 | 0.6895 | 0.6795 | 0.6652 | 0.7054 |
| 0.2852 | 5.0 | 15900 | 0.7023 | 0.7109 | 0.6810 | 0.6767 | 0.7123 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2