distilbert-base-uncased-lora-text-classification
This model is used for Sentimental Analysis and given an input will return Positive or Negative
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1550
- Accuracy: {'accuracy': 0.883}
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- 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 | 250 | 0.6110 | {'accuracy': 0.832} |
| 0.4023 | 2.0 | 500 | 0.5590 | {'accuracy': 0.871} |
| 0.4023 | 3.0 | 750 | 0.5852 | {'accuracy': 0.876} |
| 0.1908 | 4.0 | 1000 | 0.8232 | {'accuracy': 0.891} |
| 0.1908 | 5.0 | 1250 | 0.9061 | {'accuracy': 0.885} |
| 0.067 | 6.0 | 1500 | 1.0293 | {'accuracy': 0.886} |
| 0.067 | 7.0 | 1750 | 1.1672 | {'accuracy': 0.879} |
| 0.0251 | 8.0 | 2000 | 1.1400 | {'accuracy': 0.881} |
| 0.0251 | 9.0 | 2250 | 1.1411 | {'accuracy': 0.882} |
| 0.0217 | 10.0 | 2500 | 1.1550 | {'accuracy': 0.883} |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for SavirD/distilbert-base-uncased-lora-text-classification
Base model
distilbert/distilbert-base-uncased