roberta-base-bne-finetuned-multi-sentiment
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the multilingual-sentiments dataset. It achieves the following results on the evaluation set:
- Loss: 0.7635
- Accuracy: 0.7222
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6192 | 1.0 | 115 | 0.6712 | 0.7099 |
0.217 | 2.0 | 230 | 0.7635 | 0.7222 |
Framework versions
- Transformers 4.35.0
- Pytorch 1.13.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for juliowaissman/roberta-base-bne-finetuned-multi-sentiment
Base model
BSC-LT/roberta-base-bneEvaluation results
- Accuracy on multilingual-sentimentsvalidation set self-reported0.722