| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - tweet_eval |
| metrics: |
| - precision |
| - recall |
| model-index: |
| - name: bert-emotion |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: tweet_eval |
| type: tweet_eval |
| config: emotion |
| split: train |
| args: emotion |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.7350080900694398 |
| - name: Recall |
| type: recall |
| value: 0.7334480130231172 |
| --- |
| |
| <!-- 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. --> |
|
|
| # bert-emotion |
|
|
| This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the tweet_eval dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1951 |
| - Precision: 0.7350 |
| - Recall: 0.7334 |
| - Fscore: 0.7341 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - 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 | Precision | Recall | Fscore | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
| | 0.8468 | 1.0 | 815 | 0.7465 | 0.7116 | 0.6096 | 0.6325 | |
| | 0.5105 | 2.0 | 1630 | 0.9035 | 0.7532 | 0.7111 | 0.7276 | |
| | 0.2492 | 3.0 | 2445 | 1.1951 | 0.7350 | 0.7334 | 0.7341 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.25.1 |
| - Pytorch 1.13.0+cu116 |
| - Datasets 2.8.0 |
| - Tokenizers 0.13.2 |
| |
