metadata
license: mit
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-osdg
results: []
xlm-roberta-base-finetuned-osdg
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6747
- Acc: 0.8296
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: 6e-07
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Acc |
|---|---|---|---|---|
| 0.552 | 1.0 | 509 | 0.6801 | 0.8229 |
| 0.5261 | 2.0 | 1018 | 0.6821 | 0.8218 |
| 0.5518 | 3.0 | 1527 | 0.6770 | 0.8246 |
| 0.4856 | 4.0 | 2036 | 0.6781 | 0.8279 |
| 0.5427 | 5.0 | 2545 | 0.6748 | 0.8318 |
| 0.5049 | 6.0 | 3054 | 0.6769 | 0.8290 |
| 0.5155 | 7.0 | 3563 | 0.6756 | 0.8307 |
| 0.503 | 8.0 | 4072 | 0.6763 | 0.8296 |
| 0.5009 | 9.0 | 4581 | 0.6741 | 0.8301 |
| 0.555 | 10.0 | 5090 | 0.6747 | 0.8296 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1