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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_20
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_lda_20_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.6838235294117647
- name: F1
type: f1
value: 0.8122270742358079
---
<!-- 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_tiny_lda_20_mrpc
This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_20](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_20) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6247
- Accuracy: 0.6838
- F1: 0.8122
- Combined Score: 0.7480
## 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: 0.001
- 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: 30
### Training results
| Training Loss | Epoch | Step | Accuracy | Combined Score | F1 | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:--------------:|:------:|:---------------:|
| 0.6805 | 1.0 | 39 | 0.6838 | 0.7480 | 0.8122 | 0.6292 |
| 0.6386 | 2.0 | 78 | 0.6838 | 0.7480 | 0.8122 | 0.6304 |
| 0.6329 | 3.0 | 117 | 0.6838 | 0.7480 | 0.8122 | 0.6240 |
| 0.6373 | 4.0 | 156 | 0.6838 | 0.7480 | 0.8122 | 0.6240 |
| 0.6361 | 5.0 | 195 | 0.6254 | 0.6838 | 0.8122 | 0.7480 |
| 0.6372 | 6.0 | 234 | 0.6244 | 0.6838 | 0.8122 | 0.7480 |
| 0.6324 | 7.0 | 273 | 0.6249 | 0.6838 | 0.8122 | 0.7480 |
| 0.6344 | 8.0 | 312 | 0.6241 | 0.6838 | 0.8122 | 0.7480 |
| 0.631 | 9.0 | 351 | 0.6279 | 0.6838 | 0.8122 | 0.7480 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3