metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: test-trainer2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: mrpc
split: validation
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.8774509803921569
- name: F1
type: f1
value: 0.9137931034482758
test-trainer2
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5858
- Accuracy: 0.8775
- F1: 0.9138
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 |
|---|---|---|---|---|---|
| No log | 1.0 | 459 | 0.3636 | 0.8407 | 0.8837 |
| 0.5278 | 2.0 | 918 | 0.3803 | 0.8603 | 0.9002 |
| 0.3064 | 3.0 | 1377 | 0.5858 | 0.8775 | 0.9138 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cpu
- Datasets 2.14.5
- Tokenizers 0.14.1