metadata
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_km_5_v2_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.6862745098039216
- name: F1
type: f1
value: 0.7935483870967742
distilbert_km_5_v2_mrpc
This model is a fine-tuned version of Hartunka/distilbert_km_5_v2 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.5962
- Accuracy: 0.6863
- F1: 0.7935
- Combined Score: 0.7399
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.6185 | 1.0 | 15 | 0.6003 | 0.6789 | 0.7904 | 0.7347 |
| 0.5391 | 2.0 | 30 | 0.5962 | 0.6863 | 0.7935 | 0.7399 |
| 0.4435 | 3.0 | 45 | 0.6493 | 0.6961 | 0.7947 | 0.7454 |
| 0.3126 | 4.0 | 60 | 0.7969 | 0.6765 | 0.7747 | 0.7256 |
| 0.1757 | 5.0 | 75 | 1.0385 | 0.6544 | 0.7504 | 0.7024 |
| 0.0809 | 6.0 | 90 | 1.3466 | 0.6838 | 0.7795 | 0.7317 |
| 0.0458 | 7.0 | 105 | 1.5137 | 0.6838 | 0.7749 | 0.7293 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1