distilbert-base-uncased-finetuned-rating-poem
This model is a fine-tuned version of distilbert-base-uncased on the poem_sentiment dataset. It achieves the following results on the evaluation set:
- Loss: 1.1902
- Accuracy: 0.8762
- F1: 0.8765
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: 8
- eval_batch_size: 8
- 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 | Accuracy | F1 |
---|---|---|---|---|---|
0.0599 | 0.45 | 50 | 1.0247 | 0.8571 | 0.8611 |
0.1257 | 0.89 | 100 | 1.1237 | 0.8571 | 0.8500 |
0.032 | 1.34 | 150 | 1.1346 | 0.8667 | 0.8567 |
0.0012 | 1.79 | 200 | 1.2181 | 0.8381 | 0.8373 |
0.0954 | 2.23 | 250 | 1.0423 | 0.8762 | 0.8667 |
0.0323 | 2.68 | 300 | 1.0560 | 0.8667 | 0.8715 |
0.0128 | 3.12 | 350 | 1.1156 | 0.8857 | 0.8809 |
0.0269 | 3.57 | 400 | 1.1702 | 0.8762 | 0.8681 |
0.0172 | 4.02 | 450 | 1.1968 | 0.8667 | 0.8678 |
0.0004 | 4.46 | 500 | 1.1906 | 0.8762 | 0.8765 |
0.0117 | 4.91 | 550 | 1.1902 | 0.8762 | 0.8765 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.2.2
- Datasets 2.12.0
- Tokenizers 0.13.2
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for VuaCoBac/distilbert-base-uncased-finetuned-rating-poem
Base model
distilbert/distilbert-base-uncasedDataset used to train VuaCoBac/distilbert-base-uncased-finetuned-rating-poem
Evaluation results
- Accuracy on poem_sentimentvalidation set self-reported0.876
- F1 on poem_sentimentvalidation set self-reported0.877