|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- rotten_tomatoes_movie_review |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- precision |
|
- recall |
|
model-index: |
|
- name: my_distilbert_model |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: rotten_tomatoes_movie_review |
|
type: rotten_tomatoes_movie_review |
|
config: default |
|
split: test |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8395872420262664 |
|
- name: F1 |
|
type: f1 |
|
value: 0.8395554737965957 |
|
- name: Precision |
|
type: precision |
|
value: 0.8398564101118846 |
|
- name: Recall |
|
type: recall |
|
value: 0.8395872420262664 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# my_distilbert_model |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the rotten_tomatoes_movie_review dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4438 |
|
- Accuracy: 0.8396 |
|
- F1: 0.8396 |
|
- Precision: 0.8399 |
|
- Recall: 0.8396 |
|
|
|
## 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: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
|
| No log | 1.0 | 267 | 0.4091 | 0.8236 | 0.8232 | 0.8270 | 0.8236 | |
|
| 0.3608 | 2.0 | 534 | 0.3945 | 0.8405 | 0.8405 | 0.8406 | 0.8405 | |
|
| 0.3608 | 3.0 | 801 | 0.4438 | 0.8396 | 0.8396 | 0.8399 | 0.8396 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.2 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.13.3 |
|
|
