transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda_50_v1_book base_model:finetune:gokulsrinivasagan/bert_tiny_lda_50_v1_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda_50_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_50_v1_book_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.7450980392156863
      name: Accuracy
    - type: f1
      value: 0.8115942028985508
      name: F1
---

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# bert_tiny_lda_50_v1_book_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_50_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_50_v1_book) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5036
- Accuracy: 0.7451
- F1: 0.8116
- Combined Score: 0.7783

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6198        | 1.0   | 15   | 0.5903          | 0.6814   | 0.7943 | 0.7378         |
| 0.5824        | 2.0   | 30   | 0.5738          | 0.6961   | 0.7961 | 0.7461         |
| 0.5393        | 3.0   | 45   | 0.5414          | 0.7181   | 0.8027 | 0.7604         |
| 0.4624        | 4.0   | 60   | 0.5351          | 0.7255   | 0.8014 | 0.7635         |
| 0.3888        | 5.0   | 75   | 0.5036          | 0.7451   | 0.8116 | 0.7783         |
| 0.3042        | 6.0   | 90   | 0.5622          | 0.7353   | 0.8015 | 0.7684         |
| 0.292         | 7.0   | 105  | 0.5952          | 0.7623   | 0.8412 | 0.8017         |
| 0.2449        | 8.0   | 120  | 0.5547          | 0.7794   | 0.8520 | 0.8157         |
| 0.2078        | 9.0   | 135  | 0.5582          | 0.7598   | 0.8350 | 0.7974         |
| 0.1773        | 10.0  | 150  | 0.6215          | 0.7574   | 0.8078 | 0.7826         |


### Framework versions

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