|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased-finetuned-sst-2-english |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: twitter_distilbert_sentiment_model |
|
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. --> |
|
|
|
# twitter_distilbert_sentiment_model |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3731 |
|
- Accuracy: 0.7445 |
|
|
|
## 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 |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 2 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.6506 | 0.2 | 100 | 0.5897 | 0.4885 | |
|
| 0.5579 | 0.4 | 200 | 0.5109 | 0.669 | |
|
| 0.475 | 0.6 | 300 | 0.4178 | 0.724 | |
|
| 0.4342 | 0.8 | 400 | 0.4080 | 0.7125 | |
|
| 0.4214 | 1.0 | 500 | 0.3867 | 0.736 | |
|
| 0.4048 | 1.2 | 600 | 0.3910 | 0.7365 | |
|
| 0.3791 | 1.4 | 700 | 0.3858 | 0.7405 | |
|
| 0.3793 | 1.6 | 800 | 0.3779 | 0.745 | |
|
| 0.3752 | 1.8 | 900 | 0.3722 | 0.7445 | |
|
| 0.3422 | 2.0 | 1000 | 0.3731 | 0.7445 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
