transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda base_model:finetune:gokulsrinivasagan/bert_tiny_lda model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.6911764705882353
      name: Accuracy
    - type: f1
      value: 0.8067484662576686
      name: F1
---

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# bert_tiny_lda_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5813
- Accuracy: 0.6912
- F1: 0.8067
- Combined Score: 0.7490

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6373        | 1.0   | 15   | 0.6101          | 0.6838   | 0.8122 | 0.7480         |
| 0.6076        | 2.0   | 30   | 0.6006          | 0.6814   | 0.7917 | 0.7365         |
| 0.5784        | 3.0   | 45   | 0.5813          | 0.6912   | 0.8067 | 0.7490         |
| 0.5573        | 4.0   | 60   | 0.5932          | 0.6691   | 0.7644 | 0.7168         |
| 0.5109        | 5.0   | 75   | 0.6034          | 0.6446   | 0.7339 | 0.6893         |
| 0.4618        | 6.0   | 90   | 0.6813          | 0.6201   | 0.6751 | 0.6476         |
| 0.4486        | 7.0   | 105  | 0.7275          | 0.6912   | 0.8043 | 0.7478         |
| 0.3704        | 8.0   | 120  | 0.6932          | 0.6789   | 0.7745 | 0.7267         |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
