transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_lda_5_v1 base_model:finetune:gokulsrinivasagan/distilbert_lda_5_v1 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_lda_5_v1
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_5_v1_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.6985294117647058
      name: Accuracy
    - type: f1
      value: 0.7973640856672158
      name: F1
---

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# distilbert_lda_5_v1_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_5_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5926
- Accuracy: 0.6985
- F1: 0.7974
- Combined Score: 0.7479

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6456        | 1.0   | 15   | 0.5943          | 0.7059   | 0.8131 | 0.7595         |
| 0.568         | 2.0   | 30   | 0.5926          | 0.6985   | 0.7974 | 0.7479         |
| 0.5058        | 3.0   | 45   | 0.6138          | 0.7206   | 0.8167 | 0.7687         |
| 0.4158        | 4.0   | 60   | 0.6650          | 0.6789   | 0.7698 | 0.7243         |
| 0.2835        | 5.0   | 75   | 0.8592          | 0.6348   | 0.7306 | 0.6827         |
| 0.1558        | 6.0   | 90   | 1.0081          | 0.6887   | 0.7894 | 0.7391         |
| 0.0761        | 7.0   | 105  | 1.2879          | 0.6936   | 0.7826 | 0.7381         |


### Framework versions

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