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---
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: 0.8480300187617261
- name: F1
type: f1
value: 0.8480214592727926
- name: Precision
type: precision
value: 0.8481084411583488
- name: Recall
type: recall
value: 0.8480300187617261
---
<!-- 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: 0.4452
- Accuracy: 0.8480
- F1: 0.8480
- Precision: 0.8481
- Recall: 0.8480
## 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 | 0.4094 | 0.8246 | 0.8241 | 0.8281 | 0.8246 |
| 0.3518 | 2.0 | 534 | 0.4000 | 0.8508 | 0.8508 | 0.8510 | 0.8508 |
| 0.3518 | 3.0 | 801 | 0.4452 | 0.8480 | 0.8480 | 0.8481 | 0.8480 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
|