metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: finetuned_token_2e-05_16_02_2022-01_30_30
results: []
finetuned_token_2e-05_16_02_2022-01_30_30
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: 0.1748
- Precision: 0.3384
- Recall: 0.3492
- F1: 0.3437
- Accuracy: 0.9442
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: 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 | 38 | 0.3180 | 0.0985 | 0.1648 | 0.1233 | 0.8643 |
| No log | 2.0 | 76 | 0.2667 | 0.1962 | 0.2698 | 0.2272 | 0.8926 |
| No log | 3.0 | 114 | 0.2374 | 0.2268 | 0.3005 | 0.2585 | 0.9062 |
| No log | 4.0 | 152 | 0.2305 | 0.2248 | 0.3247 | 0.2657 | 0.9099 |
| No log | 5.0 | 190 | 0.2289 | 0.2322 | 0.3166 | 0.2679 | 0.9102 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3