| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: finetuning-sentiment-model-5000-samples |
| | 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. --> |
| |
|
| | # finetuning-sentiment-model-5000-samples |
| |
|
| | This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.0701 |
| | - Accuracy: 0.758 |
| | - F1: 0.7580 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | | No log | 1.0 | 313 | 1.0216 | 0.744 | 0.744 | |
| | | 0.2263 | 2.0 | 626 | 1.0701 | 0.758 | 0.7580 | |
| | | 0.2263 | 3.0 | 939 | 1.3097 | 0.723 | 0.723 | |
| | | 0.1273 | 4.0 | 1252 | 1.4377 | 0.743 | 0.743 | |
| | | 0.051 | 5.0 | 1565 | 1.4884 | 0.739 | 0.739 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.19.2 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.2.2 |
| | - Tokenizers 0.12.1 |
| |
|
