NLI-Lora-Fine-Tuning-10K-Roberta
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7314
- Accuracy: 0.6795
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 312 | 1.0705 | 0.4207 |
| 1.1119 | 2.0 | 624 | 1.0411 | 0.4660 |
| 1.1119 | 3.0 | 936 | 0.9899 | 0.5193 |
| 1.0398 | 4.0 | 1248 | 0.9264 | 0.5667 |
| 0.9603 | 5.0 | 1560 | 0.8394 | 0.6222 |
| 0.9603 | 6.0 | 1872 | 0.7944 | 0.6380 |
| 0.8749 | 7.0 | 2184 | 0.7575 | 0.6665 |
| 0.8749 | 8.0 | 2496 | 0.7439 | 0.6689 |
| 0.822 | 9.0 | 2808 | 0.7331 | 0.6795 |
| 0.8073 | 10.0 | 3120 | 0.7314 | 0.6795 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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