DistilBertLoRa
This model is a fine-tuned version of distilbert-base-uncased on the IMDB Movie dataset. It achieves the following results on the evaluation set:
- Loss: 1.0234
- Accuracy: {'accuracy': 0.884}
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 | 0.4076 | {'accuracy': 0.876} |
0.429 | 2.0 | 500 | 0.3507 | {'accuracy': 0.863} |
0.429 | 3.0 | 750 | 0.5018 | {'accuracy': 0.881} |
0.2304 | 4.0 | 1000 | 0.7036 | {'accuracy': 0.864} |
0.2304 | 5.0 | 1250 | 0.8113 | {'accuracy': 0.862} |
0.1136 | 6.0 | 1500 | 0.8428 | {'accuracy': 0.882} |
0.1136 | 7.0 | 1750 | 0.9134 | {'accuracy': 0.89} |
0.0153 | 8.0 | 2000 | 0.9723 | {'accuracy': 0.884} |
0.0153 | 9.0 | 2250 | 1.0225 | {'accuracy': 0.884} |
0.0089 | 10.0 | 2500 | 1.0234 | {'accuracy': 0.884} |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for Abdo36/DistilBertLoRa
Base model
distilbert/distilbert-base-uncased