metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: rating_prediction_model
results: []
rating_prediction_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6080
- Accuracy: 0.4022
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2129 | 0.5 | 221 | 1.9791 | 0.3623 |
| 1.9749 | 1.0 | 442 | 1.9713 | 0.3681 |
| 1.8605 | 1.5 | 663 | 1.9283 | 0.3856 |
| 1.8295 | 2.0 | 884 | 1.8659 | 0.3952 |
| 1.5815 | 2.5 | 1105 | 2.0720 | 0.3453 |
| 1.5545 | 3.01 | 1326 | 2.0883 | 0.4167 |
| 1.3294 | 3.51 | 1547 | 2.2009 | 0.3976 |
| 1.2954 | 4.01 | 1768 | 2.3456 | 0.3961 |
| 1.0684 | 4.51 | 1989 | 2.6093 | 0.4058 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2