bert-large-mnli-3ep / README.md
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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SEED0042
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: MNLI
type: ''
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.8572592969943963
---
<!-- 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. -->
# SEED0042
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: 0.5092
- Accuracy: 0.8573
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: not_parallel
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4736 | 1.0 | 12271 | 0.4213 | 0.8372 |
| 0.3248 | 2.0 | 24542 | 0.4055 | 0.8538 |
| 0.1571 | 3.0 | 36813 | 0.5092 | 0.8573 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu113
- Datasets 2.1.0
- Tokenizers 0.11.6