metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- rotten_tomatoes
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased_rotten_tomatoes
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: rotten_tomatoes
type: rotten_tomatoes
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8405253283302064
distilbert-base-uncased_rotten_tomatoes
This model is a fine-tuned version of distilbert-base-uncased on the rotten_tomatoes dataset. It achieves the following results on the evaluation set:
- Loss: 0.9770
- Accuracy: 0.8405
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: 5e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4274 | 1.0 | 534 | 0.3831 | 0.8452 |
| 0.2256 | 2.0 | 1068 | 0.5080 | 0.8405 |
| 0.1048 | 3.0 | 1602 | 0.7442 | 0.8368 |
| 0.0503 | 4.0 | 2136 | 0.8985 | 0.8443 |
| 0.0187 | 5.0 | 2670 | 0.9770 | 0.8405 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2