distilbert-finetuned-tweet-eval
This model is a fine-tuned version of distilbert-base-uncased on an tweet_eval/irony dataset. It achieves the following results on the evaluation set:
- Loss: 0.7944
- Accuracy: 0.6480
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: 9.345135299518317e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 13
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 45 | 0.6137 | 0.6649 |
| No log | 2.0 | 90 | 0.6282 | 0.6869 |
| No log | 3.0 | 135 | 0.7045 | 0.7079 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for iaminhridoy/distilbert-finetuned-tweet-eval
Base model
distilbert/distilbert-base-uncased