metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert-sst2-mahtab
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.8979357798165137
- name: F1
type: f1
value: 0.9010011123470522
distilbert-sst2-mahtab
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5766
- Accuracy: 0.8979
- F1: 0.9010
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1802 | 1.0 | 8419 | 0.4982 | 0.8830 | 0.8833 |
| 0.0987 | 2.0 | 16838 | 0.5416 | 0.8979 | 0.9025 |
| 0.0534 | 3.0 | 25257 | 0.5766 | 0.8979 | 0.9010 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3