license: apache-2.0 | |
tags: | |
- generated_from_trainer | |
datasets: | |
- imdb | |
metrics: | |
- accuracy | |
- f1 | |
model-index: | |
- name: finetuning-sentiment-model-3000-samples | |
results: | |
- task: | |
name: Text Classification | |
type: text-classification | |
dataset: | |
name: imdb | |
type: imdb | |
config: plain_text | |
split: train | |
args: plain_text | |
metrics: | |
- name: Accuracy | |
type: accuracy | |
value: 0.8733333333333333 | |
- name: F1 | |
type: f1 | |
value: 0.8733333333333333 | |
<!-- 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-3000-samples | |
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.3135 | |
- Accuracy: 0.8733 | |
- F1: 0.8733 | |
## 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 | |
- num_epochs: 2 | |
### Training results | |
### Framework versions | |
- Transformers 4.22.2 | |
- Pytorch 1.12.1+cu113 | |
- Datasets 2.5.2 | |
- Tokenizers 0.12.1 | |