---
license: mit
tags:
- generated_from_trainer
model-index:
- name: mnli_IndE
  results: []
---

<!-- 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. -->

# mnli_IndE

This model is a fine-tuned version of [WillHeld/roberta-base-mnli](https://huggingface.co/WillHeld/roberta-base-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5406
- Acc: 0.8536

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Acc    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.3901        | 0.17  | 2000  | 0.4456          | 0.8354 |
| 0.3758        | 0.33  | 4000  | 0.4508          | 0.8356 |
| 0.3668        | 0.5   | 6000  | 0.4372          | 0.8425 |
| 0.3653        | 0.67  | 8000  | 0.4357          | 0.8400 |
| 0.3543        | 0.83  | 10000 | 0.4030          | 0.8517 |
| 0.3559        | 1.0   | 12000 | 0.4242          | 0.8472 |
| 0.2523        | 1.17  | 14000 | 0.4746          | 0.8464 |
| 0.2521        | 1.33  | 16000 | 0.4780          | 0.8470 |
| 0.2525        | 1.5   | 18000 | 0.4664          | 0.8507 |
| 0.2464        | 1.67  | 20000 | 0.4806          | 0.8484 |
| 0.2495        | 1.83  | 22000 | 0.4868          | 0.8464 |
| 0.2451        | 2.0   | 24000 | 0.4794          | 0.8508 |
| 0.1737        | 2.17  | 26000 | 0.5492          | 0.8491 |
| 0.1727        | 2.33  | 28000 | 0.5552          | 0.8531 |
| 0.1736        | 2.5   | 30000 | 0.5418          | 0.8515 |
| 0.1746        | 2.67  | 32000 | 0.5511          | 0.8516 |
| 0.1717        | 2.83  | 34000 | 0.5406          | 0.8536 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1