transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/tinybert_train_book_v2 base_model:finetune:gokulsrinivasagan/tinybert_train_book_v2 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/tinybert_train_book_v2
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: tinybert_train_book_v2_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: 0.819935691318328
      name: F1
---

<!-- 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. -->

# tinybert_train_book_v2_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/tinybert_train_book_v2](https://huggingface.co/gokulsrinivasagan/tinybert_train_book_v2) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5565
- Accuracy: 0.7255
- F1: 0.8199
- Combined Score: 0.7727

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6258        | 1.0   | 15   | 0.6008          | 0.6936   | 0.8092 | 0.7514         |
| 0.5875        | 2.0   | 30   | 0.5684          | 0.7157   | 0.8159 | 0.7658         |
| 0.5354        | 3.0   | 45   | 0.5565          | 0.7255   | 0.8199 | 0.7727         |
| 0.463         | 4.0   | 60   | 0.5646          | 0.7059   | 0.7770 | 0.7414         |
| 0.3584        | 5.0   | 75   | 0.5854          | 0.7721   | 0.8463 | 0.8092         |
| 0.2647        | 6.0   | 90   | 0.6195          | 0.7647   | 0.8378 | 0.8013         |
| 0.1931        | 7.0   | 105  | 0.7031          | 0.7647   | 0.8356 | 0.8002         |
| 0.1698        | 8.0   | 120  | 0.7911          | 0.7647   | 0.8442 | 0.8044         |


### Framework versions

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