| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert/distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: finetuning-sentiment-model-distil-finalVersion |
| 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-distil-finalVersion |
|
|
| This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6034 |
| - Precision Negative: 0.8333 |
| - Recall Negative: 0.5556 |
| - F1 Negative: 0.6667 |
| - Precision Neutral: 0.75 |
| - Recall Neutral: 0.9 |
| - F1 Neutral: 0.8182 |
| - Precision Positive: 0.8462 |
| - Recall Positive: 0.7857 |
| - F1 Positive: 0.8148 |
| - Accuracy: 0.7907 |
| - Confusion Matrix: [[20, 14, 2], [2, 72, 6], [2, 10, 44]] |
|
|
| ## 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: 32 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 6 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision Negative | Recall Negative | F1 Negative | Precision Neutral | Recall Neutral | F1 Neutral | Precision Positive | Recall Positive | F1 Positive | Accuracy | Confusion Matrix | |
| |:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:-----------------:|:--------------:|:----------:|:------------------:|:---------------:|:-----------:|:--------:|:--------------------------------------:| |
| | 0.9478 | 1.0 | 22 | 0.9752 | 0.0 | 0.0 | 0.0 | 0.5064 | 0.9875 | 0.6695 | 0.875 | 0.25 | 0.3889 | 0.5407 | [[0, 35, 1], [0, 79, 1], [0, 42, 14]] | |
| | 0.7207 | 2.0 | 44 | 0.6483 | 0.8667 | 0.3611 | 0.5098 | 0.6847 | 0.95 | 0.7958 | 0.8913 | 0.7321 | 0.8039 | 0.7558 | [[13, 21, 2], [1, 76, 3], [1, 14, 41]] | |
| | 0.4066 | 3.0 | 66 | 0.6153 | 0.7586 | 0.6111 | 0.6769 | 0.7308 | 0.95 | 0.8261 | 1.0 | 0.6964 | 0.8211 | 0.7965 | [[22, 14, 0], [4, 76, 0], [3, 14, 39]] | |
| | 0.2355 | 4.0 | 88 | 0.6367 | 0.8 | 0.5556 | 0.6557 | 0.7170 | 0.95 | 0.8172 | 0.9756 | 0.7143 | 0.8247 | 0.7907 | [[20, 16, 0], [3, 76, 1], [2, 14, 40]] | |
| | 0.1048 | 5.0 | 110 | 0.5976 | 0.8333 | 0.5556 | 0.6667 | 0.75 | 0.9 | 0.8182 | 0.8462 | 0.7857 | 0.8148 | 0.7907 | [[20, 14, 2], [2, 72, 6], [2, 10, 44]] | |
| | 0.0745 | 6.0 | 132 | 0.6034 | 0.8333 | 0.5556 | 0.6667 | 0.75 | 0.9 | 0.8182 | 0.8462 | 0.7857 | 0.8148 | 0.7907 | [[20, 14, 2], [2, 72, 6], [2, 10, 44]] | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
