| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: distilbert-base-uncased_finetuned_disaster_tweets | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # distilbert-base-uncased_finetuned_disaster_tweets | |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.4007 | |
| - Accuracy: 0.8399 | |
| - F1: 0.8384 | |
| ## 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: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| | 0.4594 | 1.0 | 191 | 0.4059 | 0.8163 | 0.8164 | | |
| | 0.3399 | 2.0 | 382 | 0.3905 | 0.8346 | 0.8333 | | |
| | 0.2859 | 3.0 | 573 | 0.4007 | 0.8399 | 0.8384 | | |
| ### Framework versions | |
| - Transformers 4.25.1 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.8.0 | |
| - Tokenizers 0.13.2 | |