metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_token_itr0_1e-05_webDiscourse_01_03_2022-15_10_39
results: []
distilBERT_token_itr0_1e-05_webDiscourse_01_03_2022-15_10_39
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5867
- Precision: 0.0119
- Recall: 0.0116
- F1: 0.0118
- Accuracy: 0.6976
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 10 | 0.5730 | 0.0952 | 0.0270 | 0.0421 | 0.7381 |
No log | 2.0 | 20 | 0.5755 | 0.0213 | 0.0135 | 0.0165 | 0.7388 |
No log | 3.0 | 30 | 0.5635 | 0.0196 | 0.0135 | 0.016 | 0.7416 |
No log | 4.0 | 40 | 0.5549 | 0.0392 | 0.0270 | 0.032 | 0.7429 |
No log | 5.0 | 50 | 0.5530 | 0.0357 | 0.0270 | 0.0308 | 0.7438 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3