metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-finetuned-WebClassification-v2-smalllinguaESv2
results: []
roberta-finetuned-WebClassification-v2-smalllinguaESv2
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: 1.3862
- Accuracy: 0.6909
- F1: 0.6909
- Precision: 0.6909
- Recall: 0.6909
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 | 28 | 2.9841 | 0.2 | 0.2000 | 0.2 | 0.2 |
| No log | 2.0 | 56 | 2.8109 | 0.1636 | 0.1636 | 0.1636 | 0.1636 |
| No log | 3.0 | 84 | 2.5334 | 0.3455 | 0.3455 | 0.3455 | 0.3455 |
| No log | 4.0 | 112 | 2.1164 | 0.5273 | 0.5273 | 0.5273 | 0.5273 |
| No log | 5.0 | 140 | 1.9152 | 0.5818 | 0.5818 | 0.5818 | 0.5818 |
| No log | 6.0 | 168 | 1.6678 | 0.6182 | 0.6182 | 0.6182 | 0.6182 |
| No log | 7.0 | 196 | 1.5647 | 0.6545 | 0.6545 | 0.6545 | 0.6545 |
| No log | 8.0 | 224 | 1.4473 | 0.6727 | 0.6727 | 0.6727 | 0.6727 |
| No log | 9.0 | 252 | 1.3862 | 0.6909 | 0.6909 | 0.6909 | 0.6909 |
| No log | 10.0 | 280 | 1.3647 | 0.6909 | 0.6909 | 0.6909 | 0.6909 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3