metadata
license: apache-2.0
base_model: distilbert-base-cased
tags:
- simplification
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: finetuned_sentiment_analysis_model_yelp
results: []
finetuned_sentiment_analysis_model_yelp
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8819
- Precision: 0.6435
- Recall: 0.6438
- F1: 0.6435
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.8693 | 1.0 | 3657 | 0.8631 | 0.6183 | 0.6197 | 0.6183 |
| 0.7493 | 2.0 | 7314 | 0.8451 | 0.6358 | 0.6361 | 0.6350 |
| 0.5914 | 3.0 | 10971 | 0.8819 | 0.6435 | 0.6438 | 0.6435 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1