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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_lda_100_v1_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7083333333333334
    - name: F1
      type: f1
      value: 0.7986463620981388
---

<!-- 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. -->

# distilbert_lda_100_v1_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_100_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_100_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5833
- Accuracy: 0.7083
- F1: 0.7986
- Combined Score: 0.7535

## 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   | 0.5942          | 0.6961   | 0.7905 | 0.7433         |
| 0.5826        | 2.0   | 30   | 0.5833          | 0.7083   | 0.7986 | 0.7535         |
| 0.5649        | 3.0   | 45   | 0.6127          | 0.7034   | 0.8207 | 0.7621         |
| 0.5344        | 4.0   | 60   | 0.5919          | 0.6912   | 0.7684 | 0.7298         |
| 0.4336        | 5.0   | 75   | 0.6949          | 0.7206   | 0.8230 | 0.7718         |
| 0.3053        | 6.0   | 90   | 0.7441          | 0.6936   | 0.7731 | 0.7334         |
| 0.1738        | 7.0   | 105  | 0.9240          | 0.6887   | 0.7728 | 0.7308         |


### Framework versions

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