metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-sst2-midterm
results: []
distilbert-base-uncased-finetuned-sst2-midterm
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: 0.3341
- Accuracy: 0.9048
- F1: 0.9048
- F1 0 Class: 0.9022
- F1 1 Class: 0.9073
- Precision 0 Class: 0.9097
- Precision 1 Class: 0.9002
- Recall 0 Class: 0.8949
- Recall 1 Class: 0.9144
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | F1 0 Class | F1 1 Class | Precision 0 Class | Precision 1 Class | Recall 0 Class | Recall 1 Class |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4244 | 1.0 | 109 | 0.2882 | 0.8842 | 0.8841 | 0.8790 | 0.8889 | 0.9017 | 0.8688 | 0.8575 | 0.9099 |
| 0.2289 | 2.0 | 218 | 0.2641 | 0.8922 | 0.8922 | 0.8889 | 0.8953 | 0.8995 | 0.8855 | 0.8785 | 0.9054 |
| 0.1517 | 3.0 | 327 | 0.3000 | 0.8933 | 0.8934 | 0.8930 | 0.8937 | 0.8798 | 0.9072 | 0.9065 | 0.8806 |
| 0.1048 | 4.0 | 436 | 0.3217 | 0.8991 | 0.8990 | 0.8952 | 0.9027 | 0.9126 | 0.8870 | 0.8785 | 0.9189 |
| 0.0767 | 5.0 | 545 | 0.3341 | 0.9048 | 0.9048 | 0.9022 | 0.9073 | 0.9097 | 0.9002 | 0.8949 | 0.9144 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2