metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: finetuned_token_itr0_3e-05_essays_16_02_2022-21_02_59
results: []
finetuned_token_itr0_3e-05_essays_16_02_2022-21_02_59
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: 0.2374
- Precision: 0.4766
- Recall: 0.5549
- F1: 0.5127
- Accuracy: 0.9173
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: 3e-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 | 11 | 0.4155 | 0.1569 | 0.3168 | 0.2099 | 0.8163 |
| No log | 2.0 | 22 | 0.3584 | 0.3827 | 0.5725 | 0.4587 | 0.8691 |
| No log | 3.0 | 33 | 0.3483 | 0.4353 | 0.5649 | 0.4917 | 0.8737 |
| No log | 4.0 | 44 | 0.3187 | 0.4403 | 0.5916 | 0.5049 | 0.8770 |
| No log | 5.0 | 55 | 0.3188 | 0.4463 | 0.6031 | 0.5130 | 0.8806 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3