metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: distilbert-base-uncased
model-index:
- name: distilbert-amazon-shoe-reviews_ubuntu
results: []
distilbert-amazon-shoe-reviews_ubuntu
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: 0.9573
- Accuracy: 0.5726
- F1: [0.62998761 0.45096564 0.49037037 0.55640244 0.73547094]
- Precision: [0.62334478 0.45704118 0.47534706 0.5858748 0.72102161]
- Recall: [0.63677355 0.4450495 0.5063743 0.52975327 0.75051125]
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.9617 | 1.0 | 2813 | 0.9573 | 0.5726 | [0.62998761 0.45096564 0.49037037 0.55640244 0.73547094] | [0.62334478 0.45704118 0.47534706 0.5858748 0.72102161] | [0.63677355 0.4450495 0.5063743 0.52975327 0.75051125] |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1