metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: tweet_sentiment_analysis_clean_tweet
results: []
tweet_sentiment_analysis_clean_tweet
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4886
- Accuracy: 0.8081
- F1: 0.8073
- Recall: 0.8037
- Precision: 0.8110
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: 64
- eval_batch_size: 64
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.4077 | 1.0 | 20000 | 0.4019 | 0.8153 | 0.8177 | 0.8281 | 0.8076 |
| 0.3382 | 2.0 | 40000 | 0.4175 | 0.8148 | 0.8133 | 0.8063 | 0.8204 |
| 0.2948 | 3.0 | 60000 | 0.4528 | 0.8107 | 0.8129 | 0.8220 | 0.8041 |
| 0.2541 | 4.0 | 80000 | 0.4886 | 0.8081 | 0.8073 | 0.8037 | 0.8110 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0