|
--- |
|
license: apache-2.0 |
|
base_model: distilbert/distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert-base-cased-finetuned-feelings-text-classifier-eng |
|
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-base-cased-finetuned-feelings-text-classifier-eng |
|
|
|
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: 0.3930 |
|
- Accuracy: 0.9186 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.3309 | 1.0 | 564 | 0.2348 | 0.9193 | |
|
| 0.193 | 2.0 | 1128 | 0.2359 | 0.9226 | |
|
| 0.1566 | 3.0 | 1692 | 0.2517 | 0.9241 | |
|
| 0.1275 | 4.0 | 2256 | 0.2629 | 0.9256 | |
|
| 0.1021 | 5.0 | 2820 | 0.3023 | 0.9219 | |
|
| 0.0834 | 6.0 | 3384 | 0.3145 | 0.9193 | |
|
| 0.0679 | 7.0 | 3948 | 0.3338 | 0.9219 | |
|
| 0.0543 | 8.0 | 4512 | 0.3695 | 0.9194 | |
|
| 0.0475 | 9.0 | 5076 | 0.3795 | 0.9198 | |
|
| 0.0389 | 10.0 | 5640 | 0.3930 | 0.9186 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
