pytorch bert text-classification en transformers generated_from_trainer license:apache-2.0 model-index
---
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: SST2
      type: ''
      args: sst2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5091743119266054
---

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# SEED0042

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6996
- Accuracy: 0.5092

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: not_parallel
- gradient_accumulation_steps: 16
- 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: 600
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2104 | 0.7985          | 0.5092   |
| 0.481         | 2.0   | 4208 | 0.7191          | 0.5092   |
| 0.7017        | 3.0   | 6312 | 0.6996          | 0.5092   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu113
- Datasets 2.1.0
- Tokenizers 0.11.6
