|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: distilbert-tweet_eval-emotion |
|
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-tweet_eval-emotion |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6404 |
|
- Accuracy: 0.6529 |
|
- Precision: 0.8110 |
|
- Recall: 0.6529 |
|
- F1: 0.6507 |
|
- Auroc: 0.9184 |
|
|
|
## 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: 1e-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 |
|
- training_steps: 1000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auroc | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
|
| 0.7228 | 0.55 | 500 | 0.7232 | 0.6030 | 0.5625 | 0.6030 | 0.5760 | 0.8937 | |
|
| 0.64 | 1.1 | 1000 | 0.6404 | 0.6529 | 0.8110 | 0.6529 | 0.6507 | 0.9184 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.1 |
|
|
