Intel and Hugging Face Partner to Democratize Machine Learning Hardware Acceleration
juliensimon
• • 2distilbert-amazon-shoe-reviews
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9524
- Accuracy: 0.579
- F1: [0.62880121 0.47009599 0.50419753 0.55847134 0.73663068]
- Precision: [0.63086233 0.46744983 0.4887506 0.58988159 0.72372965]
- Recall: [0.62675351 0.47277228 0.52065273 0.53023706 0.75 ]
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 14