sentiment_xlm_roberta
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: 0.6912
- Accuracy: 0.6995
- F1: 0.6609
- Precision: 0.6453
- Recall: 0.7306
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.8513 | 1.0 | 94 | 0.9274 | 0.4043 | 0.4402 | 0.5647 | 0.6058 |
0.7096 | 2.0 | 188 | 0.6788 | 0.6938 | 0.6501 | 0.6327 | 0.7153 |
0.6114 | 3.0 | 282 | 0.7407 | 0.6635 | 0.6350 | 0.6273 | 0.7221 |
0.5379 | 4.0 | 376 | 0.6912 | 0.6995 | 0.6609 | 0.6453 | 0.7306 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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