transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_base_lda_train_book base_model:finetune:gokulsrinivasagan/distilbert_base_lda_train_book license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_base_lda_train_book
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_base_lda_train_book_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.7254901960784313
      name: Accuracy
    - type: f1
      value: 0.8028169014084507
      name: F1
---

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# distilbert_base_lda_train_book_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_base_lda_train_book](https://huggingface.co/gokulsrinivasagan/distilbert_base_lda_train_book) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5436
- Accuracy: 0.7255
- F1: 0.8028
- Combined Score: 0.7642

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6244        | 1.0   | 15   | 0.5959          | 0.6863   | 0.8000 | 0.7431         |
| 0.561         | 2.0   | 30   | 0.5541          | 0.7181   | 0.8074 | 0.7628         |
| 0.4677        | 3.0   | 45   | 0.5436          | 0.7255   | 0.8028 | 0.7642         |
| 0.3408        | 4.0   | 60   | 0.6418          | 0.7598   | 0.8444 | 0.8021         |
| 0.1934        | 5.0   | 75   | 0.9616          | 0.7304   | 0.8302 | 0.7803         |
| 0.1231        | 6.0   | 90   | 0.8708          | 0.7328   | 0.8149 | 0.7739         |
| 0.0744        | 7.0   | 105  | 1.2582          | 0.7402   | 0.8354 | 0.7878         |
| 0.0448        | 8.0   | 120  | 1.0701          | 0.7353   | 0.8118 | 0.7736         |


### Framework versions

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