---
license: mit
tags:
- generated_from_trainer
model-index:
- name: mnli_CollSgE
  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_CollSgE

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: 0.5544
- Acc: 0.8501

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4124        | 0.17  | 2000  | 0.4689          | 0.8311 |
| 0.4013        | 0.33  | 4000  | 0.4615          | 0.8321 |
| 0.3867        | 0.5   | 6000  | 0.4457          | 0.8369 |
| 0.3807        | 0.67  | 8000  | 0.4278          | 0.8422 |
| 0.3728        | 0.83  | 10000 | 0.4383          | 0.8404 |
| 0.3702        | 1.0   | 12000 | 0.4330          | 0.8437 |
| 0.2664        | 1.17  | 14000 | 0.5176          | 0.8424 |
| 0.2657        | 1.33  | 16000 | 0.5198          | 0.8433 |
| 0.2731        | 1.5   | 18000 | 0.4909          | 0.8403 |
| 0.2689        | 1.67  | 20000 | 0.4771          | 0.8448 |
| 0.2648        | 1.83  | 22000 | 0.4692          | 0.8482 |
| 0.2641        | 2.0   | 24000 | 0.4924          | 0.8503 |
| 0.1858        | 2.17  | 26000 | 0.5522          | 0.8469 |
| 0.1872        | 2.33  | 28000 | 0.5566          | 0.8487 |
| 0.1893        | 2.5   | 30000 | 0.5387          | 0.8475 |
| 0.1874        | 2.67  | 32000 | 0.5605          | 0.8491 |
| 0.1824        | 2.84  | 34000 | 0.5544          | 0.8501 |


### Framework versions

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