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---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_km_20_v1_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7132352941176471
- name: F1
type: f1
value: 0.8186046511627907
---
<!-- 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. -->
# bert_base_km_20_v1_mrpc
This model is a fine-tuned version of [Hartunka/bert_base_km_20_v1](https://huggingface.co/Hartunka/bert_base_km_20_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5820
- Accuracy: 0.7132
- F1: 0.8186
- Combined Score: 0.7659
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6264 | 1.0 | 15 | 0.6000 | 0.7108 | 0.8109 | 0.7608 |
| 0.5604 | 2.0 | 30 | 0.5820 | 0.7132 | 0.8186 | 0.7659 |
| 0.4642 | 3.0 | 45 | 0.6451 | 0.6863 | 0.7785 | 0.7324 |
| 0.3411 | 4.0 | 60 | 0.7176 | 0.6838 | 0.7741 | 0.7290 |
| 0.1998 | 5.0 | 75 | 0.9085 | 0.6912 | 0.7864 | 0.7388 |
| 0.1089 | 6.0 | 90 | 1.1335 | 0.6005 | 0.6895 | 0.6450 |
| 0.0526 | 7.0 | 105 | 1.4105 | 0.6471 | 0.7447 | 0.6959 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1