finetuning-sentiment-model-5000-samples
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: 0.3309
- Accuracy: 0.9156
- F1: 0.9436
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 254 | 0.2906 | 0.8844 | 0.9263 |
| 0.2482 | 2.0 | 508 | 0.2648 | 0.9067 | 0.9371 |
| 0.2482 | 3.0 | 762 | 0.3114 | 0.92 | 0.9472 |
| 0.1236 | 4.0 | 1016 | 0.3309 | 0.9156 | 0.9436 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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