metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-finetuned-WebClassification-v2-smalllinguaES
results: []
roberta-finetuned-WebClassification-v2-smalllinguaES
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: 1.2410
- Accuracy: 0.6471
- F1: 0.6471
- Precision: 0.6471
- Recall: 0.6471
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 9 | 2.3023 | 0.0588 | 0.0588 | 0.0588 | 0.0588 |
| No log | 2.0 | 18 | 2.0337 | 0.2353 | 0.2353 | 0.2353 | 0.2353 |
| No log | 3.0 | 27 | 1.8946 | 0.4706 | 0.4706 | 0.4706 | 0.4706 |
| No log | 4.0 | 36 | 1.7548 | 0.5882 | 0.5882 | 0.5882 | 0.5882 |
| No log | 5.0 | 45 | 1.6002 | 0.5294 | 0.5294 | 0.5294 | 0.5294 |
| No log | 6.0 | 54 | 1.4561 | 0.5294 | 0.5294 | 0.5294 | 0.5294 |
| No log | 7.0 | 63 | 1.3614 | 0.5294 | 0.5294 | 0.5294 | 0.5294 |
| No log | 8.0 | 72 | 1.2781 | 0.5882 | 0.5882 | 0.5882 | 0.5882 |
| No log | 9.0 | 81 | 1.2420 | 0.5882 | 0.5882 | 0.5882 | 0.5882 |
| No log | 10.0 | 90 | 1.2410 | 0.6471 | 0.6471 | 0.6471 | 0.6471 |
Framework versions
- Transformers 4.27.3
- Pytorch 2.0.0+cpu
- Datasets 2.10.1
- Tokenizers 0.13.2