distilbert-base-uncased-finetuned-tweet_eval_sentiment
This model is a fine-tuned version of distilbert-base-uncased on the tweet_eval dataset. It achieves the following results on the evaluation set:
- Loss: 0.6947
- Accuracy: 0.6876
- F1: 0.6871
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.6741 | 1.0 | 1426 | 0.6890 | 0.6888 | 0.6862 |
0.5239 | 2.0 | 2852 | 0.6947 | 0.6876 | 0.6871 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.0
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Dataset used to train HSIEN1009/distilbert-base-uncased-finetuned-tweet_eval_sentiment
Evaluation results
- Accuracy on tweet_evalself-reported0.688
- F1 on tweet_evalself-reported0.687