finetuned-Sentiment-classfication-ROBERTA-Base-model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6758
- Rmse: 0.5982
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse |
|---|---|---|---|---|
| 0.3238 | 2.0 | 500 | 0.6758 | 0.5982 |
| 0.2412 | 4.0 | 1000 | 0.7698 | 0.5948 |
| 0.1352 | 6.0 | 1500 | 1.1570 | 0.6736 |
| 0.0711 | 8.0 | 2000 | 1.3633 | 0.6019 |
| 0.0365 | 10.0 | 2500 | 1.4536 | 0.5986 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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