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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mnli
metrics:
- accuracy
model-index:
- name: '42'
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: MNLI
type: glue
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.8633723892002038
---
<!-- 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. -->
# 42
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8447
- Accuracy: 0.8634
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: not_parallel
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4274 | 1.0 | 12272 | 0.3892 | 0.8524 |
| 0.2844 | 2.0 | 24544 | 0.4079 | 0.8565 |
| 0.1589 | 3.0 | 36816 | 0.5033 | 0.8527 |
| 0.0877 | 4.0 | 49088 | 0.6624 | 0.8576 |
| 0.0426 | 5.0 | 61360 | 0.8447 | 0.8634 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu113
- Datasets 2.7.1
- Tokenizers 0.11.6
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