metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
results: []
results
This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1401
- Accuracy: 0.9583
- Precision: 0.9621
- Recall: 0.9583
- F1: 0.9586
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: 9.755035812704661e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 0.2914 | 0.875 | 0.9038 | 0.875 | 0.8757 |
| No log | 2.0 | 14 | 0.2127 | 0.9583 | 0.9621 | 0.9583 | 0.9586 |
| No log | 3.0 | 21 | 0.1401 | 0.9583 | 0.9621 | 0.9583 | 0.9586 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1